Abstract

   ADAR1 edits double-stranded RNAs (dsRNAs) by deaminating adenosines
   into inosines, preventing aberrant activation of innate immunity by
   endogenous dsRNAs, which may resemble viral structures. Several tumors
   exploit ADAR1 to evade immune surveillance; indeed, its deletion
   reduces tumor viability and reshapes infiltrating leukocytes. Here we
   investigated the role of ADAR1 in immune evasion mechanisms during
   cervical cancer (CC) progression. Patients’ biopsy samples showed
   higher ADAR1 expression already in premalignant lesions (squamous
   intraepithelial lesions [SIL]) and a substantially reduced percentage
   of infiltrating CD7^+ innate cells in in situ and invasive carcinomas
   compared with normal mucosa, with CD56^+ NK cells showing phenotypic
   alterations that may have affected their functional responses. In
   CC-derived cell lines (SiHa, CaSki), ADAR1 silencing reduced cell
   proliferation, an effect further enhanced by exogenous IFN-β
   administration. It also induced proinflammatory gene expression, as
   demonstrated by RNA-Seq analysis, and conditioned supernatants
   collected from these cells activated several NK cell effector
   functions. NK cell infiltration and activation were also confirmed in
   organotypic 3D tissue models of SiHa cells knocked out for ADAR1. In
   conclusion, ADAR1 expression increased with CC progression and was
   accompanied by alterations in tumor-infiltrating NK cells, but its
   silencing in CC-derived cell lines potentiated antitumor NK cell
   activities. Thus, ADAR1 inhibition may represent a therapeutic
   perspective for CC and possibly other malignancies.

   Keywords: Immunology, Inflammation, Oncology

   Keywords: Cervical cancer, Innate immunity, NK cells
     __________________________________________________________________

   <span>Targeting ADAR1 in cervical cancer suppresses proliferation and
   induces proinflammatory factors, promoting NK cell activation. This
   </span><span>might represent </span><span>an immunostimulatory approach
   beyond cervical cancer patients.</span>

Introduction

   Cervical cancer (CC) is the fourth leading cause of cancer-related
   mortality in women ([62]1). It takes years or decades to develop, and
   it is distinguished by a spontaneous continuous progression, starting
   with a persistent intraepithelial human papillomavirus (HPV) infection
   in almost all cases, evolving to squamous intraepithelial lesions
   (SILs) and then into invading tumors and metastasis ([63]2). Although
   prophylactic vaccines are available, a large portion of the population
   remains unvaccinated, and the vaccine does not prevent cancer
   development in individuals already exposed to the virus ([64]3).

   From an immunological perspective, CC is classified as an
   immune-infiltrated yet immunosuppressive malignancy. Despite the
   presence of an antitumor immune response, its effectiveness is often
   compromised during disease progression, primarily due to HPV-mediated
   modulation of the tumor microenvironment (TME) ([65]3, [66]4).

   Indeed, effective evasion of immune recognition seems to be the
   hallmark of HPV infections already at earlier stages, as the virus is
   almost invisible to the immune system due to an exclusively
   intraepithelial infectious cycle — with no viremic phase and no
   virus-induced cell death — and viral replication and release are not
   associated with inflammation. In addition, HPV downregulates innate
   immune signaling pathways; proinflammatory cytokines, particularly type
   I interferons (IFN-Is), are not released and the signals for
   antigen-presenting cell activation and recruitment are either not
   present or inadequate. This immune ignorance results in chronic
   infections that persist over weeks and months. Progression to
   high-grade SIL (HSIL) is associated with further deregulation of
   immunologically relevant molecules — particularly chemotactic
   chemokines and their receptors — on keratinocytes and endothelial cells
   of the underlying microvasculature, limiting or preventing infiltration
   of cytotoxic effectors into the lesion ([67]5, [68]6).

   NK cells are innate lymphocytes with a critical cytotoxic and
   immunoregulatory role, and although they are disseminated in the
   uterine mucosa, their role in the natural history of HPV infection and
   HPV-driven tumorigenesis is not entirely clear. It was reported that
   they emerge at an early stage in HPV-infected lesions and NK cells are
   present at higher level in premalignant lesions with a lower viral load
   ([69]7). In studies of individuals with confirmed SILs of different
   grades, lesion regression strongly correlated with early infiltration
   of intraepithelial effector cytotoxic cells (granzymeB^+CD8^+
   [GzmB^+CD8^+] and GzmB^+CD56^+) ([70]8, [71]9). More recent studies
   applying single-cell multi-omics technologies provided new in-depth
   maps of the complex CC ecosystem ([72]10–[73]14). One common
   characteristic was the observation of an increased NK cell infiltrate
   in the tumor area, often (but not always) accompanied by an enriched
   cytotoxicity signature (e.g., GZMB, GZMH, PRF1), higher expression of
   genes involved in migration and adhesion, and lower levels of
   inhibitory molecules (e.g., TIGIT, CTLA-4). Moreover, expression of
   some of these genes was associated with a better prognosis
   ([74]11–[75]13), consistent with the observation that patients with CC
   with a high level of intratumoral NK cells had a decreased risk of
   progression ([76]10). Interestingly, in one of these studies, the
   heterogeneity of malignant cells was investigated in relation to TME.
   Among the different cellular states uncovered, one was characterized by
   a bidirectional tumor stroma–immune system interaction involving NK and
   T cells through IFN signaling ([77]14). However, to the best of our
   knowledge, beyond such transcriptomic approaches, other studies
   analyzing the phenotype of infiltrating NK cell subsets or of other
   innate lymphoid cells (ILCs) isolated from patients’ biopsy samples are
   lacking.

   Over the last 15 years, several populations of ILCs have been described
   and classified into 5 groups (NK cells, ILC1, ILC2, ILC3, and LTi)
   according to their transcription factors (TFs) and cytokine production
   profile ([78]15). In particular, NK cells are historically identified
   as CD56^+CD16^+/–CD127^–EOMES^+ ([79]13). Although ILCs are now
   emerging as important players in numerous tumor types, their role has
   not been thoroughly investigated in either intraepithelial lesions or
   invasive carcinomas (ICs) of the cervix.

   Antitumor responses are also dependent on IFNs, and loss of IFN
   signaling results in resistance to immune checkpoint therapies
   ([80]16–[81]19). Expression of IFN-I can be induced by long, fully
   base-paired dsRNAs deriving from viruses, but also by certain
   endogenous self RNAs that could aberrantly stimulate innate immune
   responses ([82]20, [83]21). To prevent an erroneous activation of
   cytosolic sensors by self dsRNAs, ADAR1 — a member of the adenosine
   deaminase acting on RNA (ADAR) family of enzymes — edits such dsRNAs
   ([84]20–[85]22) by deaminating adenosines to inosines (A-to-I
   conversion), which are subsequently read out as guanosines, leading to
   transcriptomic and proteomic changes ([86]20). Indeed, in many types of
   tumors, a substantial amount of mutational load is due to RNA
   editing/hyperediting by ADAR1 ([87]21, [88]23). Moreover, recent
   studies demonstrate that ADAR1 deletion reduces cancer cell viability
   via IFN-I pathway activation ([89]24, [90]25), and in ADAR1-null
   tumors, there is a global reshaping of immune cell profiles, suggesting
   that inflammation caused by ADAR1 deletion can bypass the loss of
   tumor-specific CD8^+ T cells ([91]19, [92]26). This evidence is in line
   with the fact that ADAR1 is considered a “master regulator” of
   cytoplasmic innate immunity, as it prevents autoimmunity ([93]22).
   Indeed, in humans, loss-of-function mutations of ADAR1 can confer
   severe interferonopathies and autoimmune diseases ([94]27).

   There are few studies on the role of ADAR1 in HPV-driven tumorigenesis.
   An increase in expression was associated with CC progression ([95]28,
   [96]29), and its ablation correlated with a proinflammatory phenotype
   ([97]30), while a particular ADAR1 haplotype was related to recurrent
   dysplasia in patients coinfected with HPV/HIV ([98]31). However,
   whether ADAR1 affects NK/ILC effector functions is not known, and to
   our knowledge, the interplay among ADAR1, IFN-I, and NK cells has not
   been previously addressed in any tumor model, including CC. Thus, in
   our study we investigated whether ADAR1 plays a role in CC
   tumorigenesis via its ability to dampen IFN-I signaling and production,
   with potential effects on NK/ILC-mediated innate immune responses as
   well.

Results

ADAR1 expression correlates with disease progression in CC.

   To determine the importance of ADAR1 in the progression of CC, we first
   asked whether ADAR1 expression can represent a prognostic factor for
   patients’ survival. TCGA data revealed that high ADAR1 levels were
   predictive of poor overall patient survival ([99]Figure 1A), and R2:
   Genomics Analysis and Visualization Platform data also showed a
   significant progressive increase in ADAR1 expression from normal
   tissues to SIL to IC ([100]Figure 1B). These initial findings were
   confirmed by real-time PCR (RT-PCR) performed on mRNA extracted from
   formalin-fixed, paraffin-embedded tissues derived from normal mucosa,
   low-grade SIL (LSIL), or IC biopsies. Indeed, ADAR1 expression
   increased markedly during disease progression ([101]Figure 1C).
   Additional analysis of TCGA data for ADAR1 expression in ICs at
   different stages of the disease revealed a tendency toward increased
   ADAR1 expression from stage I to stage IV, which was associated with a
   significant decrease in interferon-stimulated gene (ISG) expression in
   more advanced tumors ([102]Figure 1D and [103]Supplemental Table 1;
   supplemental material available online with this article;
   [104]https://doi.org/10.1172/jci.insight.190244DS1).

Figure 1. ADAR1 overexpression characterizes CC progression.

   [105]Figure 1
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   (A) Kaplan-Meier survival plot for CC patients (n = 292) stratified by
   low (red line) and high (blue line) ADAR1 expression (cutoff mode:
   scan). Data were obtained from TCGA. For survival analysis, statistical
   significance was assessed with the log-rank test. (B) ADAR1 expression
   was assayed on single HG_U133A arrays. Gene Expression Omnibus database
   (GEO [107]GSE7803). (C) Total RNA was extracted from paraffin-embedded
   biopsy samples, and ADAR1 expression was analyzed by RT-PCR. (D) ADAR
   expression (left panel) and ISG core score (right panel) at different
   clinical stages in the TCGA data. Between-group P values were computed
   using Wilcoxon’s rank-sum test. bonf, Bonferroni post hoc test; f.i,
   fold increase; Pt. patient Ctr, normal mucosa; IC, invasive CC.

   Expression of ADAR1 in CC progression was further investigated by IHC
   on a panel of paraffin-embedded tissue samples ([108]Figure 2). While
   ADAR1 was almost undetectable in normal mucosa ([109]Figure 2A, a and
   b), its expression increased noticeably during disease progression,
   with clear positivity already in the LSIL ([110]Figure 2A, panels c and
   d). Thus, we compared ADAR1 expression with the proliferative index
   pattern of Ki-67, which is routinely used to aid diagnosis in
   morphologically difficult cases, for example between LSIL and reactive
   or metaplastic lesions ([111]32). In certain cases, we found similar
   expression patterns of ADAR1 and Ki-67, with basal and parabasal layer
   positivity in LSILs, which indicated that ADAR1 positivity was related
   to an increase in proliferative index, although it was limited to the
   lower epithelial layers ([112]Figure 2B). ADAR1 expression further
   increased during disease progression ([113]Figure 2A, panels e–j) and
   extended to the upper layer of squamous epithelium, and Ki-67 showed a
   similar distribution pattern, alongside p16, a surrogate marker of HPV
   infection and high-grade dysplasia (data not shown).

Figure 2. Expression of ADAR1 in normal cervical mucosa, premalignant
lesions, and CCs.

   [114]Figure 2
   [115]Open in a new tab

   (A) Expression of ADAR1 on normal mucosa (immunostains; original
   magnification, 5× and 20×) (a and b), premalignant lesions (LSIL) (c
   and d), and invasive CCs (e–j) (immunostains; original magnification,
   8× top row; 20× bottom row) was analyzed by IHC. (B) Representative
   images of IHC staining of ADAR1 compared with Ki-67 expression on LSIL
   lesions (immunostains; original magnification, 8× and 10×). (C)
   Quantification (%) of cytoplasmic (cyt) and nuclear (nuc) ADAR1
   expression in the different lesions (17 LSIL, 10 HSIL/CIS, 41 IC). (D)
   Quantification (%) of total ADAR1 in G2–G3 IC stained sections. P
   values were calculated by ANOVA. (E) Expression of total ADAR1^+ cells
   in G2 and G3 lesions with low numbers of infiltrating CD56^+ cells
   (CD56^+ <5). The P value was calculated by ANOVA. *P < 0.05, **P <
   0.01.

   We also investigated whether the increasing expression of ADAR1 was
   accompanied by changes in its staining pattern, since ADAR1 is
   localized in the nucleus and/or the cytoplasm. We observed that in
   HSIL/in situ carcinomas (HSIL/CISs) and in ICs, ADAR1 showed
   cytoplasmic positivity significantly different from that in LSILs
   ([116]Figure 2C). Moreover, there was a decrease in nuclear positivity,
   particularly between LSIL and CIS. Within the same group of lesions,
   the increase in cytoplasmic versus nuclear expression was statistically
   significant in CIS and IC, but not in LSIL ([117]Figure 2C, P = 0.004
   in CIS; P = 0.017 in IC). ADAR1 expression was even more evident in
   high-grade (grade 3 [G3]) compared with G2 CC ([118]Figure 2D),
   although our consideration was semiquantitative.

   Considering our interest in tumor-infiltrating innate lymphocytes, in
   more aggressive tumors we also examined the presence of cells
   expressing CD56, a well-known NK cell marker. Separating tumors on the
   basis of a low (CD56^+ <5) or not low (CD56^+ >5) number of positive
   cells, we observed a significantly higher percentage of ADAR1^+ cells
   in G3 tumors in the group with low CD56^+ cells ([119]Figure 2E).
   Together, these results showed increasing expression of ADAR1 during
   disease progression from LSIL to HSIL/CIS and IC. Moreover, in samples
   from the latter group of patients, ADAR1 expression was even higher in
   G3 compared with G2 tumors, with a significant difference also
   maintained when lesions with low CD56^+ cells were analyzed.

Decreased levels of tumor-infiltrating ILCs are observed in CC.

   To further investigate immune cells infiltrating cervical lesions, we
   analyzed the proportion of ILCs isolated from fresh biopsy samples
   obtained from different groups of patients ([120]Figure 3). In situ and
   invasive carcinomas were grouped together and compared with LSILs, as
   well as with normal mucosa used as control. Total leukocytes were
   identified as CD45^+ cells, and within them innate lymphocytes were
   gated as CD7^+ and negative for T cell (CD3, CD4, CD5), B cell (CD19),
   and monocyte (CD14) markers. Although an increased percentage of
   infiltrating CD45^+ cells characterized both LSIL (44%) and CIS/IC
   (37%) compared with normal mucosa (32%), the frequency of innate CD7^+
   lymphocytes was significantly decreased in CIS/IC (from ~8% in normal
   mucosa, to ~7% in LSIL, and to ~3% in CIS/IC) ([121]Figure 3, B and C).
   We further characterized CD7^+ cells to discriminate between NK, ILC1,
   ILC2, and ILC3 cell populations. In humans, the distinction between NK
   and ILC1 cells can be challenging, but it is widely accepted that
   tissue ILC1, ILC2, and ILC3 cells can be identified by the expression
   of IL-7Ra (CD127) in combination with group-specific TFs: EOMES, GATA3,
   and RORγt, respectively. Analysis of CD7^+ infiltrating lymphocytes
   showed a very low percentage (0%–5%) of CD127^+ cells regardless of the
   biopsy sample analyzed and undetectable GATA3 and RORγt expression,
   thus ruling out the presence of ILC2 and ILC3 populations. On the other
   hand, approximately 60% of CD7^+ cells coexpressed the NK marker CD56
   and the NK TF EOMES, leading to their identification as NK cells,
   although no marked differences were detected between control mucosa,
   LSIL, and CIS/IC samples ([122]Figure 3, A and D, and data not shown).
   However, we noticed a significantly lower percentage when more
   aggressive (G3) ICs were analyzed (~60% in G3 versus ~80% in G2)
   ([123]Figure 3E).

Figure 3. Analysis of innate immune cells infiltrating LSIL, HSIL/CIS, and
IC.

   [124]Figure 3
   [125]Open in a new tab

   Fresh biopsy samples obtained from different groups of patients were
   analyzed for the presence of an innate immune cell infiltrate. (A)
   Gating strategy from representative FACS plots, showing the isolation
   of (left to right panel) live cells, CD45^+ cells (gate excludes
   monocytes), and Lin^–CD7^+ ILCs (middle right panel), further divided
   according to CD56, CD127, EOMES, and CD103 expression. ILCs were thus
   defined as Lin^–CD45^+CD7^+ and then separated into NK/ILC1, ILC2, and
   ILC3 subpopulations (see the main text for more details). (B and C) Bar
   graphs represent the percentage of CD45^+ (B) and CD7^+ (C) cells among
   each group of patients. HSIL/CIS and IC biopsy samples were grouped
   together (CIS/IC, red triangles) and compared with LSIL or normal
   mucosa used as control. (D and E) Bar graphs represent the percentage
   of CD56^+ cells among the Lin^–CD45^+CD7^+cells in the different groups
   of patients (D) and in G2/G3 tumors (E). (F) Bar graphs represent the
   percentage of distinct subsets expressing or not CD56 and CD103.
   Histograms represent mean ± SEM. *P < 0.05, **P < 0.01. Two-way ANOVA
   was used for multiple comparisons. Each symbol represents a single
   biopsy sample.

   NK cells can recirculate from blood to tissues, where they can be
   quickly recruited during viral infection or tumor growth, and, as with
   other lymphocytes, their tissue retention is facilitated by CD69, CD103
   (αE integrin), and CD49a expression. Therefore, to investigate the
   possible tissue-resident nature of infiltrating NK cells, we further
   analyzed CD7^+ cells for expression of CD103 in combination with CD56
   ([126]Figure 3F). There was a general rise in CD103^+ cells in CIS/IC
   biopsy samples, with a statistically significant difference reached in
   the CD56^– subset (with a 3-fold increase compared with normal mucosa
   or LSIL). This increase was accompanied by a statistically significant
   decrease in the CD103^–CD56^– subset (from ~55% in LSIL to ~20% in
   CIS/IC). These cells were, however, NK cells, as they maintained
   expression of the typical NK markers EOMES and CD94.

   We further broadened the phenotypic characterization of the CD56/CD103
   subset and assessed expression of some activating/inhibitory receptors
   (CD16, NKG2D, NKp46, NKp44, NKp30, KIR, CD94, Tigit) and adhesion
   (CD49a) and cytotoxic molecules (GzmB and GzmK). The major modulations
   were observed in the CD56^+ cell subsets, where an increase in the
   expression of CD49a, CD94 and NKp44 alongside a decrease in the
   activating receptor CD16 and in GzmB expression characterized
   CIS/IC-infiltrating cells ([127]Figure 4).

Figure 4. Phenotypic characterization of ILC1/NK cell subsets during CC
progression.

   [128]Figure 4
   [129]Open in a new tab

   MFI of selected marker expression by distinct subsets (CD56^+CD103^–,
   CD56^+CD103^+, CD56^–CD103^+, and CD56^–CD103^–). Histograms represent
   mean ± SEM. *P < 0.05, **P < 0.01. Two-way ANOVA was used for multiple
   comparisons. Each symbol represents a single biopsy sample.

   Collectively, these data suggest that the innate CD7^+ lymphocytes
   infiltrating the uterine cervix were NK cells, and their frequency
   appears to have been reduced in more aggressive G3 tumors. They also
   highlight the role of the TME in shaping their phenotype by promoting
   the acquisition of tissue-resident features (CD103, CD49) and/or by
   impacting effector functions through alterations of the cells’
   activating receptor expression profile and cytotoxic molecule content.

ADAR1 silencing in CC-derived cell lines induces the expression of
IFN-stimulated genes and affects cell proliferation.

   As our results demonstrated not only increased ADAR1 expression during
   CC progression but also a reduction in NK cell infiltration in tumors,
   we aimed to establish an in vitro system to better investigate the
   impact of ADAR1 expression on innate lymphocytes, particularly NK
   cells. Data from the Cancer Cell Line Encyclopedia (CCLE) allowed us to
   select CC-derived cells suitable for our experiments. Based on
   expression pattern and z score, indicating the gene’s expression level
   compared with the mean in each cell line, we selected SiHa and CaSki
   cells among those with higher and lower levels of ADAR1 expression,
   respectively ([130]Supplemental Figure 1, A and B).

   Next we sought to determine whether SiHa and CaSki cells exhibited
   ADAR1 dependency in terms of survival by analyzing available
   CRISPR/Cas9 datasets ([131]24), and according to The Cancer Dependency
   Map (DepMap), ADAR1 appeared to have an essential function in both cell
   lines (Chronos score < –0.5) ([132]Supplemental Figure 1C).

   To investigate the effects of ADAR1 manipulation on CC-derived cells
   and on innate immune cells and pathways, we set up an in vitro system
   where ADAR1 expression was transiently inhibited by specific siRNA
   (siADAR1). ADAR1 silencing in both SiHa and CaSki cell lines showed a
   knockdown efficiency of approximately 50%–70%, as demonstrated by
   RT-PCR and immunoblot analysis. As expected, a consequence of ADAR1
   depletion was induction of a type I IFN response, evidenced both by an
   increase in IFNβ transcript levels and by PKR phosphorylation at
   Thr446/Thr451 residues ([133]Supplemental Figure 2, A and B).

   We then investigated the ADAR1 dependency of SiHa and CaSki cells by
   long-term proliferation assays using the Incucyte imaging system, which
   showed a decrease in proliferative activity of ADAR1-silenced cells in
   both cell lines ([134]Figure 5, C and D). As loss of ADAR1 can cause
   both cell-intrinsic lethality (e.g., via high levels of ISGs, including
   PKR) and induction of key antitumor cytokines, including IFN-I, we
   asked whether administration of IFN-I in the context of ADAR1 loss
   would further limit cell proliferation ([135]24). Both cell lines were
   treated with IFN-β, starting 3 days after siRNAs transfection (day 0)
   and up to 5 days ([136]Figure 5, A and B), and cell proliferation was
   then measured. Indeed, in the presence of IFN-β, both ADAR1-silenced
   cell lines were sensitive to the treatment, as their proliferative
   capacity was even further inhibited compared with that of all other
   combinations ([137]Figure 5, C and D).

Figure 5. Effects of IFN-β on CC-derived cell proliferation upon ADAR1
silencing.

   [138]Figure 5
   [139]Open in a new tab

   SiHa and CaSki cell lines were transfected with an ADAR1 siRNA for 72
   hours (considered as day 0), then treated with IFN-β (1,000 IU/mL) for
   several days. ADAR1 expression was analyzed by immunoblotting after 48
   hours on SiHa (A) or CaSki (B) cells. (C and D) Proliferation was
   monitored up to 5 days by Incucyte Live-Cell Analysis, analyzed for
   cell confluence, and expressed as fold change (FC) normalized to the
   scan time 0 (T0) set as 1, using Incucyte Zoom software. Proliferation
   index was calculated by setting cells at T0 as 1 (arbitrary index
   [A.I.]). Results from one representative experiment and pooled data
   from 4 independent experiments (mean ± SEM) are shown. *P < 0.05, **P <
   0.01.

   To further explore other relevant changes in gene expression profiles
   caused by ADAR1 silencing, we performed an RNA-Seq analysis
   ([140]Supplemental Figure 3). Inhibition of ADAR1 resulted in increased
   expression of 1,410 and 829 genes in SiHa and CaSki cells,
   respectively, while 1,540 and 346 genes were downmodulated (logFC > 1;
   FDR < 0.05) ([141]Supplemental Figure 3, A and B). Among the induced
   genes, we could identify numerous ISGs, including several
   proinflammatory cytokines and chemokines involved in the regulation of
   innate lymphocytes, including NK cells (e.g., CXCL8, CXCL9/10/11, CCL5,
   IL12, IL18, IL6) ([142]Supplemental Figure 3, C and D). KEGG pathway
   enrichment analysis showed similar functional enrichment signatures,
   confirming the activation of several pathways related to the
   inflammatory response, such as cytokine–cytokine receptor interaction,
   NF-kB signaling pathway, and TNF signaling pathway ([143]Supplemental
   Figure 3, E and F).

   Overall, these data suggest that ADAR1 inhibition in CC cells can cause
   both a constraint of their cell-proliferative capacity and upregulation
   of proinflammatory cytokines and chemokines associated with innate
   immunity and antitumor effects.

Conditioned medium from ADAR1-silenced CC-derived cell lines enhances NK cell
effector functions.

   In view of the induction of IFN-I, ISGs, and proinflammatory factors
   observed in the transcriptomic analysis of ADAR1-silenced cells, we
   asked whether conditioned media (CM) collected from these cells could
   influence NK cell effector functions. Thus, CM from siADAR1 or siCtr
   SiHa and CaSki cells were collected at 72–96 hours after transfection
   and then used to stimulate NK cells. First, freshly purified NK cells
   were incubated with CM, and their proliferative capacity was analyzed
   for several days by the Incucyte imaging system. The results showed a
   significantly higher rate of NK cell proliferation in the presence of
   siADAR1- compared with siCtr-derived cell supernatants ([144]Figure
   6A).

Figure 6. ADAR1 inhibition enhances NK cell functions.

   [145]Figure 6
   [146]Open in a new tab

   Conditioned media (CM) from siCtr^– and siADAR1-transfected SiHa and
   CaSki cells were harvested after 72 hours and used in different assays.
   (A) CM from SiHa and CaSki cells was incubated for the indicated time
   points with purified NK cells isolated from healthy donors.
   Proliferation was measured by Incucyte Live-Cell Analysis and analyzed
   with Incucyte Zoom software. Proliferation index was calculated as fold
   change by setting Nuclight-positive NK cells at scan 0 (T0) as 1
   (A.I.). Pooled data are from 3 independent experiments with NK cells
   from 7 different donors. (B) NK cell degranulation was evaluated by
   FACS using the lysosomal marker CD107a. Purified NK cells were used as
   effectors and treated with CM from SiHa or CaSki cells for 18 hours and
   then cocultured with SiHa (left panel) or K562 (middle and right
   panels) cells, used as targets (E/T ratio of 1:2). CD107a expression
   was evaluated on NK cells gated as CD56^+. Pooled data are from 3
   independent experiments with NK cells from 6 (target SiHa) or 7 (target
   K562) different donors. (C) Migration of cultured (cNK) or primary
   (pNK) purified NK cells was measured using a Transwell migration
   chamber. As chemoattractant, SiHa and CaSki CM was added to the lower
   compartment, and after 2–4 hours at 37°C, the migrated cells were
   counted using BD FACSCanto. Pooled data are from at least 2 independent
   experiments with 7 different donors. All data are expressed as mean ±
   SEM. Statistical analysis was performed by paired t test. *P < 0.05,
   **P < 0.01, ***P < 0.001, ****P < 0.0001.

   Then, we determined the effects of CM on NK cell–mediated killing.
   Freshly isolated and purified NK cells were cultured overnight with
   different CM and then used as effector cells in degranulation assays.
   As targets, we used either the same CC-derived cell line from which the
   CM was collected or K562 cells, the prototypic target of human NK
   cell–mediated killing. As an indicator of NK cell degranulation, the
   expression of the widely used marker CD107a was evaluated by FACS
   analysis gating on viable CD56^+ NK cells after 4 hours of incubation
   with target cells. As shown in [147]Figure 6B, NK cells stimulated with
   siADAR1 CM derived from SiHa cells showed a higher level of
   degranulation against SiHa or K562 cells compared with NK cells
   incubated with siCtr CM. Similarly, siADAR1 CM derived from CaSki cells
   activated NK cell degranulation against K562, while CaSki cells were
   resistant, as induction of CD107a expression was always below 4% (data
   not shown). In a parallel set of experiments, we addressed the role of
   IFN-I possibly released in the supernatants of siADAR1 cells in the
   activation of NK cell degranulation. NK cells were pretreated with a
   blocking anti-IFNAR2 mAb or an isotype control IgG, then incubated with
   CM derived from SiHa cells for 18 hours and tested against K562 target
   cells. Our findings indicate that blocking the IFN-I receptor on NK
   cells resulted in statistically significant inhibition of the
   degranulation triggered by siADAR1 CM (P = 0.0014 between siADAR1/IgG
   and siADAR1/anti-IFNAR2), while it had no effect with siCtr CM
   ([148]Supplemental Figure 4A). Moreover, the effects of siCtr CM were
   similar to those observed on NK cells cultured with fresh medium. As a
   control of the blocking capacity of the anti-IFNAR2 mAb, we also tested
   the degranulation activity of NK cells previously stimulated with IFN-β
   (100 IU/mL, for 18 hours) against K562 targets ([149]Supplemental
   Figure 4B). As expected, IFN-β increased CD107a expression on NK cells,
   which was significantly inhibited by incubation with the blocking mAb
   (P = 0.0018 between IgG and anti-IFNAR2), returning to the basal levels
   observed when NK cells were cultured with fresh medium alone. No CD107a
   expression was detected when NK cells were cultured without target
   cells, independently of IFN-β stimulation. Finally, we also analyzed
   the effect of CM on NK cell migration. Primary or cultured NK cells
   incubated with supernatants from siADAR1 SiHa and CaSki cells showed an
   increased ability to migrate compared with siCtr medium–incubated cells
   ([150]Figure 6C).

   Together, the results obtained with CM from CC-derived cell lines
   suggest that inhibition of ADAR1 expression induced the release of
   IFN-I and of other soluble factors able to boost NK cell proliferation,
   killing, and migration.

ADAR1 inhibits NK cell infiltration and cytotoxic capacity in 3D organotypic
cultures.

   To further investigate the impact of ADAR1 expression on NK cell
   effector functions, we set up 3D organotypic cultures and tested the
   ability of NK cells to infiltrate the epithelial layers and induce cell
   apoptosis. Ectocervical epithelium equivalents that could efficiently
   mimic HSIL in vitro were prepared using ADAR1-KO or control SiHa cells
   ([151]Supplemental Figure 5). In [152]Figure 7A, a representative image
   of SiHa raft sections stained with H&E shows the highly irregular
   profile of the epithelial basal layer, with several events of matrix
   invasion, confirming the high invasive potential of SiHa cells. Next,
   we analyzed the ability of NK cells to infiltrate the in vitro
   generated epithelium expressing or not expressing ADAR1. To this aim,
   we initially prepared organotypic raft cultures using SiHa cells
   knocked out or not for ADAR1, and after 21 days, we added NK cells on
   the top of the cultures. Twenty-four hours after NK cell seeding, we
   performed quantitative immunofluorescence analyses using an anti-CD56
   antibody to visualize infiltrating NK cells and TUNEL assay to identify
   apoptotic nuclei. The data revealed that in ADAR1-KO cultures, the
   number of CD56^+ cells detected in the rafts was slightly but
   significantly higher than in control samples ([153]Figure 7B), and they
   appeared to be surrounded by a greater number of TUNEL-positive nuclei
   and nuclear fragments ([154]Figure 7B, insets). Quantitative analysis
   of TUNEL staining, performed using lower-magnification images for each
   sample, confirmed that ADAR1-KO cultures displayed a significant
   increase in apoptotic nuclei in the presence of NK cells, compared with
   controls ([155]Figure 7, C and D). Overall, these results suggest that
   in 3D organotypic cultures, ADAR1 depletion enhanced the ability of
   CC-derived cells to be recognized and targeted by activated NK cells.

Figure 7. Impact of ADAR1 silencing and of NK cell infiltration on SiHa cell
apoptosis in organotypic cultures.

   [156]Figure 7
   [157]Open in a new tab

   3D cultures of ectocervical squamous epithelia equivalents were
   prepared using control SiHa and SiHa ADAR1-KO cells (KO by
   CRISPR/Cas9). After 3 weeks, NK cells were added on the top of
   stratified layers and left to infiltrate for 24 hours (see Methods for
   details). Rafts were finally fixed, embedded in paraffin, and stained
   with H&E or processed for immunofluorescence and TUNEL assays. (A)
   Representative image of a SiHa raft section stained with H&E, showing
   the highly irregular basal layer of the epithelial portion and invasive
   events in the matrix counterpart (arrows). Scale bar: 40 μm. (B)
   Sections were stained using anti-CD56 antibody (red) and TUNEL (green).
   Nuclei were counterstained with DAPI. Bar graphs show the fold increase
   in infiltrating CD56^+ cells/field (mean ± SEM). Scale bar: 20 μm. (C
   and D) Sections were also quantified for TUNEL^+ cells (green) on
   low-magnification images of each sample. Bar graphs show the number of
   TUNEL^+ cells/field ± SD. Scale bar: 40 μm. Statistical analysis was
   performed by paired t test. *P < 0.05, **P < 0.01, ***P < 0.001.

Discussion

   In the present study, to investigate the mechanisms involved in the
   suppression of innate immune responses that may favor tumorigenesis, we
   explored, for the first time to our knowledge, the interplay among
   ADAR1, IFN-I, and NK cells. We focused on CC, since its progression
   from the SIL premalignant condition to in situ and then invasive
   carcinoma may span 10 to 20 years after HPV infection, thus reflecting
   a long-lasting inability of immune responses to eliminate infected
   cells and highlighting at the same time an ample window for potential
   therapeutic interventions. In this context, ADAR1 may play a central
   role by its ability to dampen IFN-I responses, which have well-known
   antitumor effects ([158]16). In fact, ADAR1 overexpression is well
   documented in several cancers, and it is correlated with clinically
   aggressive behavior and poor prognosis ([159]21). Regarding CC, despite
   the limited number of studies published to date, a similar trend
   appears to emerge, suggesting that patients with high ADAR1 expression
   have a worse prognosis ([160]28, [161]29). This scenario may be linked
   to the suppressive effects mediated by ADAR1 on the TME, as a previous
   study in other models demonstrated that loss of ADAR1 enhances tumor
   inflammation and immune cell infiltration ([162]19, [163]26).

   Investigating publicly available datasets, we indeed observed an
   inverse correlation between ADAR1 expression and patients’ overall
   survival probability, along with a progressive decrease in expression
   of a set of ISGs from stage I to stage IV tumors. These preliminary
   observations were further addressed in a panel of cervical lesions of
   different types and grades, where ADAR1 expression, while almost
   undetectable in normal mucosa, was highly enhanced in the progression
   from LSIL to IC and further increased in more aggressive, G3 tumors. We
   also noticed an alteration of its cellular distribution during SIL to
   IC progression, with a significant increase in the percentage of
   cytoplasmic ADAR1^+ cells. In this regard, it is well known that ADAR1
   undergoes alternative splicing, resulting in a constitutively expressed
   p110 short isoform primarily localized in the nucleus, and in a long
   IFN-inducible p150 isoform that can shuttle between the nucleus and the
   cytoplasm, where it predominantly resides ([164]20, [165]22). However,
   it remains to be clarified whether the variation in ADAR1 cellular
   distribution correlates with expression of a specific isoform, IFN-I
   levels in the TME, changes in the editing activity, and/or patient
   prognosis. Nevertheless, the immunoregulatory role of ADAR1 in the
   progression of CC is supported by additional observations.
   Specifically, when analyzing ADAR1 expression in G2 and G3 tumors with
   fewer infiltrating CD56^+ cells (CD56^+ < 5), we observed significantly
   higher ADAR1 expression in the more aggressive G3 lesions. Moreover,
   leukocytes isolated from fresh biopsies exhibited a progressive
   reduction in the percentage of infiltrating innate lymphocytes, from
   normal mucosa, to LSIL, and finally to tumors. These cells were
   identified as NK cells based on their expression profile (i.e.,
   Lin^–CD45^+CD7^+EOMES^+CD56^+/–), and a subset of them expressed CD103
   and CD49a tissue-resident markers and were further characterized by
   higher expression of CD94 and NKp44, as well as of the inhibitory
   receptor Tigit. Additionally, there was a reduction in CD16 and GzmB
   expression when compared with cells isolated from normal mucosa.
   Collectively, these findings suggest that NK cells infiltrating tumors
   strengthen their tissue-resident features, downregulate their main
   activating receptor and cytotoxic molecules, and increase Tigit
   inhibitory receptor, thus indicating an alteration of NK cell
   functionality. Furthermore, the significant reduction in the percentage
   of freshly isolated CD56^+ cells in G3 compared with G2 tumors,
   accompanied by our previous observations on tumor-infiltrating CD56^+
   cells in IHC analysis, may represent a feature of CC progression.
   Indeed, more recent single-cell transcriptome studies investigating the
   composition of TME during CC progression demonstrated that the impaired
   local immune landscape plays a key role in cervical carcinogenesis.
   Moreover, although to our knowledge, no data have been reported on
   other ILC populations, NK cells displayed notable stage-dependent
   differences in tumors. In general, HSILs were characterized by an
   activated TME, infiltrating effector NK cells, and a proinflammatory
   signature, while ICs showed an immunosuppressive TME with resident NK
   cells ([166]33). Of note, analysis of tumors and paired adjacent
   stromal tissues revealed a slight enrichment of the NK cell subset with
   a suppressive phenotype in the tumor area, while the subset with an
   activated cytotoxic phenotype was excluded ([167]13). TME composition
   in CC may also be influenced by treatment strategies, as single-cell
   RNA-Seq of CC biopsies before and after radiochemotherapy revealed an
   increase in CD16^+ NK cells, which exhibited an enhanced cytotoxic
   (GRZB/H) and migration (CCL5/CCR1) gene signature following therapy
   ([168]12). Integrative spatial transcriptomics and proteomics analysis
   uncovered bidirectional tumor stroma–immune system interactions, where
   malignant cells interacted with NK/T cells through IFN signaling, and
   revealed extensive cellular communications — based on
   chemokine/chemokine receptors — between tumor and immune cells,
   including NK cells ([169]14). Indeed, preliminary analysis of samples
   from a CC clinical trial ([170]NCT04516616) demonstrated that
   neoadjuvant chemotherapy (NACT) induced a state transition
   characterized by increased tumor-infiltrating immune cells, which
   correlates with response to immune-checkpoint blockade, at least partly
   through IFN activation. Therefore, some of the tumor states identified
   not only were correlated with immune cell infiltration abundance but
   might also be directly involved in recruiting immune cells. The results
   of our ex vivo analysis indicate a decrease in NK cells in more
   aggressive tumors and highlight a potential role for ADAR1 in
   modulating the TME. In fact, transcriptomic analysis on CC-derived cell
   lines revealed that ADAR1 silencing pushed cancer cells toward a
   proinflammatory phenotype through the induction of IFN-I, ISGs, and
   lymphocyte-recruiting chemokines and cytokines known to be involved in
   NK cell recruitment and activation ([171]34). Accordingly, Zhang et al.
   performed an unsupervised hierarchical clustering of various immune
   cell types in CC and identified a unique subset of patients with
   disproportionate intratumoral NK cells and a significantly lower risk
   of tumor progression ([172]10).

   We reasoned that this inflamed microenvironment triggered by ADAR1
   silencing could influence activation of NK cell functions, an aspect
   that to our knowledge has not been addressed in any tumor model.
   Indeed, exposing NK cells to CM harvested from ADAR1-silenced cells
   significantly enhanced their proliferation, killing, and migration.
   Although the role of specific cytokines/chemokines in regulating NK
   cell functions was not investigated, we believe the cooperative action
   of several factors, likely including IFN-I, may be required. Type I
   IFNs play central roles in the immune system’s defense against tumors,
   and their antitumor effects are multifaceted, involving both indirect
   and direct mechanisms such as activation/attraction of infiltrating
   immune cells and induction of apoptosis and of cell cycle arrest in
   tumor cells ([173]16). Indeed, the inhibition of SiHa and CaSki cell
   proliferation, already detectable upon ADAR1 silencing, was even more
   marked when we treated silenced cells with IFN-β. This suggests that
   ADAR1 inhibitors could synergize with existing anticancer
   immunotherapies based on IFNs and on other proinflammatory factors to
   arrest cancer progression and potentiate antitumor NK cell immune
   responses. In this context, a recent study on the B16 murine model
   demonstrated that ADAR1 suppression in cancer cells had a profound
   impact on TME and enhanced antitumor immunity, as it caused a global
   reshaping of tumor-infiltrating lymphocytes and sensitized tumors to
   immunotherapy and to IFNs ([174]19). In our model of 3D organotypic
   cultures, we also detected a significant increase in apoptotic nuclei
   in the context of ADAR1 KO and upon infiltration of NK cells. Thus, the
   possibility to boost NK cell recruitment and activation in tumors via
   ADAR1 downregulation may allow development of alternative
   antiviral/anticancer therapies.

   Regarding the initiation and progression of tumors in the cervix, while
   the role of the immune system in controlling HPV is well established,
   recent studies highlight a more complex scenario. These studies suggest
   that chronic inflammatory responses initiated by HPV-transformed cells
   can reprogram the local immune environment, thereby fueling cancer
   progression ([175]35). In fact, precancerous high-grade lesions, as
   well as invasive CCs, are frequently associated with strong
   inflammatory infiltrates in the stroma. This inflammatory milieu, while
   initially part of the body’s defense mechanism, can paradoxically
   promote tumor progression at later stages. Thus, the immune system
   emerges as a double-edged sword also in HPV-associated carcinogenesis,
   with its role changing in a stage-dependent manner. ADAR1 appears to be
   well adapted to this scenario, and we propose that — within the TME — a
   fine-tuning exists between chronic inflammation and production of
   inflammatory factors that sustain ADAR1 expression on one hand, and
   inhibition of cytokine release by ADAR1 itself on the other. Thus, our
   data suggest that induction of an acute — more than a chronic —
   inflammatory TME stimulated by ADAR1 inhibition might contribute to
   cancer cell death by inducing both cell cycle arrest and antitumor
   immune responses.

   In summary, these findings reveal a previously unrecognized role of
   ADAR1 as a potential therapeutic target affecting HPV^+ CC cells.
   Additionally, they provide proof of concept that silencing ADAR1 can be
   combined with standard chemotherapies, as well as with IFN and
   proinflammatory therapies, to enhance their antiproliferative and
   anticancer effects, potentially extending beyond CC.

Methods

   Further information is provided in [176]Supplemental Methods.

Sex as a biological variable.

   Our study exclusively examined samples from female donors, because CC
   is a disease that affects women.

Enrollment of patients and IHC stainings.

   For the retrospective study, we selected from our database 68 patients
   referred to the Department of Gynecological, Obstetrical, and
   Urological Sciences of the Umberto I Hospital in Rome between the years
   2017 and 2019. Patients had a diagnosis of LSIL (n = 17), HSIL/CIS (n =
   10), or IC (n = 41, of which 34 were squamous carcinomas and 7
   adenocarcinomas); the latter patients underwent 3 cycles of
   platinum-based NACT (weekly 30 mg/mq cisplatin plus 60 mg/mq
   paclitaxel), followed by radical hysterectomy ([177]Supplemental Table
   2). Clinical information, comprising age, clinical stage, and
   pathologic response to neoadjuvant treatment, including pathological
   staging ([178]36) and grading definition (AJCC Cancer Staging Manual,
   8th ed., 2017) were obtained from the institutional databases. Two
   experienced pathologist reviewed histological features. For diagnostic
   purposes, the diagnosis of LSIL was confirmed by Ki-67 expression on
   basal and parabasal layers of squamous epithelium, while HSIL showed
   diffuse expression of Ki-67 and overexpression of p16. Overexpression
   of p16 in infiltrating carcinomas was considered a surrogate marker of
   HPV association ([179]37, [180]38).

   Serial sections were obtained from each paraffin block for IHC
   evaluation of ADAR1 expression and CD56^+ infiltrating cells.
   Hematoxylin was used for cytoplasmic and nuclear counterstaining. ADAR1
   immunostainings were performed with mouse mAb sc-271854 (dilution
   1:100, Santa Cruz Biotechnology), using an automated immunostainer
   (BOND-MAX, Leica Microsystems) with the BOND Polymer Refine Detection
   kit according to the manufacturer’s instructions. Negative controls
   were obtained by omitting the primary antibody. A minimum of 200
   neoplastic cells were present in each biopsy sample. A positive stain
   was defined as the presence of nuclear and/or cytoplasmic staining,
   either strong or weak, complete or incomplete, in at least 1% cells.
   For each case, the staining of the entire section was
   semiquantitatively assessed using the H-score method as follows:
   H-score = (3 × percentage of tumor cells with 3^+ staining) + (2 ×
   percentage of tumor cells with 2^+ staining) + (1 × percentage of tumor
   cells with 1^+ staining), in the nucleus and/or in the cytoplasm of the
   entire section. This score, therefore, is in the range of 0 to 300.
   Evaluation of infiltrating CD56^+ cells was carried out with the
   anti-CD56 antibody (PA0191) (Bond RTU Primary, Leica Microsystems). All
   tests were evaluated independently by A. Pernazza and M. Leopizzi.

Characterization of infiltrating leukocytes in fresh biopsies.

   Fresh biopsy samples from LSIL (n = 14), HSIL/CIS (n = 10), IC (n =
   18), or normal mucosa (n = 40) were obtained from women enrolled at the
   Department of Gynecological, Obstetrical, and Urological Sciences of
   the Umberto I Hospital in Rome ([181]Supplemental Table 3), with the
   following inclusion criteria: no systemic diseases, no
   immunodeficiency, being fertile and sexually active with no current
   pregnancy, intact uterus, no use of antibiotics or vaginal
   antimicrobials in the previous month, no vaginal intercourse or vaginal
   lavage within the last 3 days, and no treatment for cervical disease or
   other sexually transmitted infections in the previous 6 months. Samples
   were obtained during surgical treatment and immediately treated for
   leukocyte isolation. Tissue samples were washed in PBS, minced with a
   scalpel, treated with Tumor Dissociation Kit solution, and processed
   with gentleMACS Octo Dissociator (all from Miltenyi Biotec) for 1 hour
   at 37°C. Cells were filtered through a 100 μm cell strainer filter and
   treated with red blood cell lysis buffer for 10 minutes at room
   temperature. Cells were then counted and stained for FACS analysis.
   Samples containing fewer than 1,000 CD45^+ cells were excluded from
   analysis due to low event count.

FACS analysis.

   Cells freshly isolated from biopsy samples were stained with antibodies
   specific for extracellular antigens and resuspended in Brilliant Stain
   Buffer (BD Horizon) for 30 minutes at 4°C. They were then fixed and
   permeabilized with FOXP3 staining buffer for 20 minutes at room
   temperature and finally stained with antibodies specific for
   intracellular antigens resuspended in the FOXP3 washing buffer for 30
   minutes at 4°C (eBioscience FOXP3/Transcription Factor Staining Buffer
   Set, Invitrogen). Fixable viability dye (BD Biosciences) was used to
   discriminate between live and dead cells; negative cells were
   considered viable. Innate lymphocytes were identified among lineage
   negative (Lin^–) (CD3^–CD14^–CD19^–CD5^–CD4^–) CD45^+CD7^+ cells. Type
   1 ILCs were identified according to CD56, CD127, EOMES, and T-BET
   expression. Sample acquisition was performed by a LRSFortessa flow
   cytometer (BD Biosciences), and data were analyzed with FlowJo
   software. A detailed list of mAbs used is provided in [182]Supplemental
   Table 4.

Cell cultures.

   SiHa, CaSki, and K562 cell lines and primary cultures of human
   fibroblasts (HFs) are described in [183]Supplemental Methods. Human NK
   cell cultures were obtained by coculturing PBMCs with irradiated
   RPMI8866 feeder cells for 8–10 days ([184]39). Primary human NK cells
   were purified from PBMCs by negative selection using the RosetteSep
   Human NK Cell Enrichment Cocktail (STEMCELL Technologies).
   Proliferation, migration, and cytotoxicity experiments were performed
   with NK cell populations that were 80%–95% CD56^+CD3^–.

siRNA and ADAR1 KO.

   CaSki (2 × 10^5) and SiHa (3 × 10^5) cells were transfected using
   Oligofectamine Transfection Reagent (Thermo Fisher Scientific) charged
   with a mixture of 3ADAR1-specific siRNAs (siADAR1) (sc-37657) or a
   nontargeting siRNA (siCtr) (sc-37007, both from Santa Cruz
   Biotechnology) (30 nM final concentration). ADAR1 gene expression
   levels were evaluated at 72–96 hours after transfection by RT-PCR or
   immunoblotting.

   SiHa ADAR1-KO cells were produced by CRISPR/Cas9 technology. The
   lentiviral system used was “GSGH11935-Edit-R All-in-one lentiviral
   sgRNA” (Horizon), where 3 different ADAR1-targeting plasmids and 3
   lentiviral vectors (GSGH11935-247534211, GSGH11935-247605059, and
   #GSGH11935-247728949) were pooled together. The plasmids contain both
   the gene for Cas9 expression and the gene encoding the RNA guide to
   target the Cas9 to the target gene. After purification from bacterial
   culture, 6 μg plasmid was transfected together with 1.25 μg pVSVG and
   3.25 μg psPAX2 plasmids — necessary for lentiviral vector production —
   into the HEK293T cells using Lipofectamine 2000 Reagent (Invitrogen).
   After 2 days of incubation at 37°C, the conditioned medium containing
   the virus was harvested, filtered, and then used to infect SiHa cells
   by centrifugation. Two infection cycles were applied by using polybrene
   (MilliporeSigma) at 4 μg/mL for the first and at 8 μg/mL for the second
   cycle, followed by 2 hours of incubation at 37°C. Infected SiHa cells
   were then kept in selection with puromycin (1 μg/mL).

RT-PCR.

   RNA was extracted from paraffin-embedded cervical biopsy samples using
   an RNeasy Plus Mini Kit (QIAGEN, 74134) following deparaffinization
   with xylene and ethanol. RNA extracted from SiHa and CaSki cells was
   purified by use of a Total RNA Mini Kit (Geneaid, RB100). After
   purification, RNAs were treated with DNase I (AMPD1, MilliporeSigma).
   The following gene-specific Taqman probes were used: ADAR1
   (Hs01017598_g1 and Hs01017601_m1), IFNbeta1 (Hs01077958_s1), GAPDH
   (Hs02758991_g1) (Thermo Scientific). Additional information is provided
   in [185]Supplemental Methods.

Immunoblotting.

   Cells were lysed in 50 mM Tris-HCl pH 7.6, 150 mM NaCl, 0.2% Triton
   X-100, 0.3% NP40, 1 mM EDTA, 50 mM NaF, 1 mM Na[3]VO[4], 1 mM PMSF, and
   a cocktail of protease and phosphatase inhibitors (MilliporeSigma).
   Total protein concentration was determined by Bio-Rad protein assay
   (BPA). Cell lysates were resolved by SDS-PAGE and blotted to
   nitrocellulose membranes. Then membranes were blocked with TBS-T (with
   0.05% Tween) containing 5% skim milk for 1 hour at room temperature and
   probed overnight with primary antibodies at 4°C. After washing,
   secondary anti-rabbit or anti-mouse antibodies (Merck) were incubated
   for 1 hour at room temperature, and immune-reactive bands were
   visualized using the ECL chemiluminescence system (Cyanagen) at the
   iBright FL1500 Imaging System (Thermo Fisher Scientific). The following
   antibodies were used: anti-ADAR1 (rabbit D7E2M, Cell Signaling
   Technology); anti–β-actin (AC15, MilliporeSigma); anti–pPKRT446 (rabbit
   ab32036, Abcam); anti-pPKRT451 (rabbit ab81303, Abcam); anti-PKR
   antibody (3072, Cell Signaling Technology).

NK cell assays.

   For proliferation, SiHa and CaSki cells were harvested 72 hours after
   silencing, seeded at a density of 5,000 cells/well in 96-well plates,
   and stimulated or not with IFN-β (1,000 IU/mL). In some experiments, CM
   from siADAR1 or siCtr cells was collected at 72–96 hours after
   transfection and used to stimulate fresh NK cells that had been labeled
   with the Incucyte Nuclight Reagent (4717, Sartorius) and grown in a
   96-well plate (40,000 cells/well) previously coated with 0.01%
   poly-l-ornithine (MilliporeSigma, P4957). Proliferation was measured by
   the Incucyte Live-Cell Analysis System, and data were analyzed with
   Incucyte Zoom software (Sartorius).

   NK cell–mediated degranulation was evaluated using the lysosomal marker
   CD107a ([186]40). Freshly isolated and purified NK cells were cultured
   for 18 hours in the presence of CM derived from siADAR1 or siCtr cells,
   then incubated with target cells at an E/T ratio of 1:2. As targets, we
   used either the same CC-derived cell line from which the CM were
   collected or K562 cells, the prototypic target for human NK
   cell–mediated killing. As negative controls, NK cells were incubated
   with fresh medium (alone or in the presence of target cells). After 4
   hours, NK cells were then stained with BD Horizon Fixable Viability
   Stain 780, anti-CD56/BV421 (562751, BD) and anti-CD107a/APC (560664,
   BD). In some experiments, NK cells were pretreated with a blocking
   anti-IFNAR2 (MilliporeSigma, MAB1155) or an isotype control mAb at 37°C
   for 30 minutes, then incubated with the CM or with IFN-β (100 IU/mL) at
   37°C for 18 hours. The mAbs used in the pretreatment were to have a
   final concentration of 1 mg/mL once NK cells were diluted).

   Migration of purified (pNK) or cultured (cNK) NK cells was measured
   using a Transwell migration chamber (6.5 mm, 5 μm; Costar). As
   chemoattractant, CM from siADAR1 or siCtr cells was normalized to cell
   number by dilution with serum-free medium and then added to the lower
   compartment. After 3–4 hours at 37°C, the migrated cells were counted
   using a FACSCanto (BD). The percentage of migrated cells was calculated
   as follows: number of migrated NK cells/number of input NK cells × 100
   ([187]41).

RNA-Seq and bioinformatic analysis.

   Bioinformatic analysis on R2, TCGA, CCLE, and DepMap Platforms are
   described in [188]Supplemental Methods. For RNA-Seq analysis, the
   library was prepared using 1.5 mcg total RNA, according to the
   manufacturer’s protocol. Samples of CaSki and SiHa cells were prepared
   with Kapa RNA HyperPrep with RiboErase (total RNA) and Kapa Globin
   Depletion Hybridization Oligos (Roche). Samples were sequenced by
   NovaSeq 6000 Sequencing System, RUN 2 × 101 bp, Illumina Instrument.
   The average number of reads obtained from each sample was 140 million.
   Post-sequencing Quality Control was performed by FastQC
   ([189]https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)
   v.0.12.1. Adapter sequences were trimmed and low-quality reads removed
   using cutadapt v3.4. Mapping of RNA and generation of gene counts were
   done using STAR ([190]42) aligner v.2.7.10b against human reference
   GRCh38 (build p13) and using feature annotation (v109) downloaded from
   the Ensembl repository. Differential Expression Analysis of
   differentially expressed genes (DEGs) was performed by edgeR v.4.0.2;
   volcano plots and heatmaps were created by ggplot2 v3.4.4 in R
   (v4.3.3), comparing 2 conditions (siCtr and siADAR). Pathway enrichment
   and network analyses for DEG lists were performed using clusterProfiler
   v.4.0 using gene sets from the KEGG pathway database, where small (<10
   genes) pathways were removed. In all statistical analysis, an effect
   was considered statistically significant if the FDR of its
   corresponding statistical test was ≤5% and considered biologically
   significant if the logFC was ≥1.

Organotypic cultures.

   3D cultures of ectocervical squamous epithelia equivalents were
   prepared using a modified version of the protocol previously applied
   for skin rafts ([191]43). Briefly, collagen rafts were prepared by
   adding 5 mg/mL rat tail type I collagen (Corning) to DMEM and
   reconstitution buffer (8:1:1). HFs (1 × 10^6) were added to 2 mL of the
   collagen mixture in polycarbonate micron inserts (23 mm, 0.3 μm;
   Corning) in 6-column deep well plates. The mixture was left to
   polymerize for 30 minutes at 37°C. After 24 hours, 2 × 10^5 SiHa or
   SiHa ADAR1-KO cells were seeded on the collagen gel and left to grow
   for 7 days in CM added in both top and bottom wells. Then organotypic
   cultures were lifted to the air-liquid interface and cultured for
   additional 2 weeks in CM. To test the ability of NK cells to infiltrate
   SiHa layers, 1 × 10^6 of cultured NK cells were added on top of the
   organotypic culture in the last 24 hours. Rafts were finally fixed in
   10% formalin and embedded in paraffin, and 4 μm slices were stained
   with H&E or processed for the immunofluorescence procedure.
   Bright-field images were taken with an Axiocam ICc 5 (Zeiss) connected
   with an Axioplan 100 microscope (Zeiss). For immunofluorescence,
   organotypic raft sections were deparaffinized and stained as previously
   described ([192]44). Primary anti-CD56 mAb (1:50 in PBS; Dako) was
   incubated for 1 hour at 25°C, followed by goat anti-mouse IgG–Texas red
   (1:200 in PBS; Jackson Immunoresearch Laboratories) for 30 minutes at
   25°C. Nuclei were stained with DAPI (1:1,000 in PBS; MilliporeSigma).
   For detection and quantification of apoptotic cells, raft sections were
   processed for TUNEL technology using an In Situ Cell Death Detection
   Kit (Roche) following the standard protocol. All fluorescence signals
   were analyzed by scanning cells with an ApoTome System (Zeiss)
   connected with an Axiovert 200 inverted microscope (Zeiss); image
   analysis was performed by Axiovision software (Zeiss). Quantitative
   analysis of TUNEL^+ nuclei and of CD56^+ cells was performed by
   analyzing 10 different microscopy fields randomly taken from 3
   independent experiments.

Statistics.

   For IHC staining, quantitative variables are described as mean and
   range, while qualitative variables are reported as number and
   percentage. Univariate associations between clinicopathological
   features and pathological response were evaluated using 1-way ANOVA,
   χ^2 test, or Pearson correlation coefficient. Multiple comparisons were
   performed using univariate ANOVA (2-way ANOVA with Bonferroni’s post
   hoc test). Some analyses were performed using IBM SPSS Statistics 25.
   In other analyses, statistical significance between groups was
   determined by performing 2-tailed Student’s t test. Prism 10 (GraphPad)
   software was used. Graphs show mean values, and error bars represent SD
   or SEM. P values less than 0.05 were considered statistically
   significant.

Study approval.

   Written informed consent in accordance with the Declaration of Helsinki
   was obtained from all patients, and approval was obtained from the
   Ethics Committee of the Sapienza University of Rome (prot. 0372/2023).

Data availability.

   Values for all data points in graphs are reported in the
   [193]Supporting Data Values file. RNA-Seq data were deposited in the
   NCBI’s Gene Expression Omnibus database (GEO [194]GSE297095).

Author contributions

   VT and MK conceptualized the study, developed the methodology,
   performed formal analysis, and wrote the original manuscript draft. SP,
   MEG, HS, and SR developed the methodology and performed formal
   analysis. VDM, ML, IP, AP, and FT collected patient samples and
   clinical information, developed methodology, and performed formal
   analysis. FB, VM, and DR developed the 3D methodology and performed
   formal analysis. LLS developed the Incucyte methodology and performed
   formal analysis. GB, MC, and AZ reviewed and edited the manuscript. CC
   and AS conceptualized and supervised the study, validated the data,
   performed formal analysis, acquired funding, administered the project,
   wrote the original draft, and reviewed and edited the manuscript.

Supplementary Material

   Supplemental data
   [195]jciinsight-10-190244-s022.pdf^ (2.3MB, pdf)
   Unedited blot and gel images
   [196]jciinsight-10-190244-s023.pdf^ (801.1KB, pdf)
   Supporting data values
   [197]jciinsight-10-190244-s024.xlsx^ (162.8KB, xlsx)

Acknowledgments