Abstract

   Hepatitis B virus (HBV) integration is strongly associated with
   hepatocellular carcinoma (HCC). However, the genetic alterations and
   pathogenesis mechanisms remain significantly unexplored, especially for
   HBV-inserted cancer-related genes. This study identified recurrent HBV
   DNA integration into the CCDC91 gene in HCC tissues (n = 17) using
   pooled analysis and HBV capture sequencing. CCDC91 expression was
   positively correlated with HBV DNA presence, and higher levels were
   linked to shorter overall survival in HCC patients. CCDC91 was
   upregulated in HCC and promoted HCC malignancy in vitro and in vivo.
   CCDC91 deficiency increased sensitivity to sorafenib treatment. By RNA
   sequencing and co-immunoprecipitation assays, we further demonstrated
   that the Ct-HBx upregulated CCDC91 and that CCDC91 induced aerobic
   glycolysis by activating LDHA to drive HCC progression. In conclusion,
   the HBV integrated gene CCDC91 is a novel HCC-related gene that
   functions through the Ct-HBx/CCDC91/LDHA axis. Our work sheds light on
   the mechanism in driving HCC progression and sorafenib resistance.

   Subject terms: Tumour biomarkers, Infectious-disease diagnostics
     __________________________________________________________________

   HBV DNA integration upregulates CCDC91, activating LDHA via glycolysis.
   CCDC91 deficiency enhances sorafenib sensitivity, highlighting its role
   as a therapeutic target in HBV-HCC.

Introduction

   Hepatocellular carcinoma (HCC) was the sixth most common cancer
   worldwide in 2020, with approximately half of all new cases originating
   in China^[38]1. While surgical resection and liver transplantation are
   viable treatments for early-stage HCC, most patients eventually succumb
   to tumor recurrence and metastasis^[39]2. HCC is the third deadliest
   malignancy globally, and it surpasses other types of cancer in terms of
   mortality for men and women. Thus, preventing and curing this disease
   is highly challenging.

   The etiology of HCC is complex and multifactorial, with chronic
   hepatitis B virus (HBV) infection being a primary cause, particularly
   in China^[40]3. Several major molecular mechanisms of
   hepatocarcinogenesis are caused by HBV infection. Recently, increasing
   evidence has indicated that HBV DNA integration plays a crucial role in
   the development of HCC^[41]4–[42]7. One significant consequence of HBV
   DNA integration into the host genome is the truncation of the HBV
   genome, especially at the C-terminus of HBx (Ct-HBx). HBx functions as
   a transcriptional transactivator that is involved in the progression of
   HBV-related HCC^[43]8. Previous studies have shown that the integrated
   HBx gene can regulate WNT-5a expression through microRNA
   modifications^[44]9,[45]10, which lead to increased cell proliferation
   in vitro and in vivo^[46]11. Recently, Zhang et al. reported that the
   Ct-HBx could mediate metabolic reprogramming from mitochondrial
   respiration to aerobic glycolysis via the NFACT2-TXNIP signaling
   pathway in hepatocarcinogenesis^[47]12. On the other hand, HBV DNA
   integration can cause genomic instability and insertional mutagenesis
   of various cancer-related genes. For instance, the human telomerase
   reverse transcriptase (TERT) gene is the most common site for HBV DNA
   integration in HCC. Li et al. demonstrated that the recurrence of HBV
   DNA integration in the TERT promoter region in HCC can activate TERT
   transcription in response to sex hormones^[48]13. Moreover, Sze et al.
   revealed that HBV integration at the TERT promoter was associated with
   increased TERT mRNA expression and more aggressive tumor behavior. They
   also demonstrated an ELF4-HBx-TERT promoter signal axis in
   hepatocarcinogenesis^[49]14. In addition to TERT, many HCC cases are
   therefore expected to have HBV integration in cyclin E1 (CCNE1).
   Doxycycline-induced expression of Ccnel in mice has demonstrated that
   Cyclin E1 overexpression leads to liver-specific molecular and cellular
   defects^[50]15. Because one third of HBV preferential target genes are
   cancer-related genes, it is believed that insertional mutagenesis may
   play a role in HCC development, and this proposal requires further
   exploration.

   Our previous study revealed that the integration of viral DNA into the
   host genome was an important mechanism for HBV-related carcinogenesis
   in HCC and in non-Hodgkin lymphoma (NHL)^[51]16. Notably, the gene
   coiled-coil domain-containing protein 91 (CCDC91) was identified as a
   recurrent target of HBV DNA integration in HCC and NHL samples. The
   coiled-coil structural domain (CCD), consisting of 2–5 intertwined
   α-helices, is widely expressed in a variety of proteins, regulates cell
   motility, and is involved in cell signaling. Recently, abnormal
   activation of CCD-containing proteins has been observed in several
   tumors^[52]17, such as CCDC178^[53]18 and CCDC34^[54]19 in HCC, CCDC88A
   in pancreatic cancer^[55]20, and CCDC8^[56]21 in lung cancer. In the
   field of cancer research, CCDC91 has not been studied as extensively as
   other CCD-containing proteins. CCDC91 is a 441 amino- acid polypeptide
   that belongs to the superfamily of coiled-coil domain-containing
   proteins and is involved in Golgi-to-lysosome transport. Variants at
   12p11, including CCDC91, have been associated with a greater risk of
   breast cancer^[57]22. In NHL, we found that patients with high
   expression of CCDC91 had poor survival, with borderline
   significance^[58]16. However, the role of CCDC91 in HCC has not been
   studied.

   Metabolic reprogramming affects the occurrence and development of
   various cancers, including HCC^[59]23. Intriguingly, in cancer cells,
   despite the presence of oxygen, a preference for glycolysis (Warburg
   effect) often results in increased lactate production and rapid
   adenosine triphosphates (ATP) generation. ATP and many molecules
   required for carcinogenesis are synthesized in cancer cells to regulate
   the tumor microenvironment, maintain cancer biology, and resist
   antitumor therapy. In this study, we identified aerobic glycolysis,
   particularly lactate dehydrogenase A (LDHA), as a downstream target of
   CCDC91 in regulating HCC proliferation and metastasis. LDHA is a key
   enzyme in the glycolytic pathway, playing a critical role in cellular
   energy metabolism. It catalyzes the conversion of pyruvate to lactate,
   a process particularly vital under hypoxic conditions where oxidative
   phosphorylation is limited. LDHA is frequently overexpressed in various
   cancers, driving this glycolytic phenotype and contributing to tumor
   progression, invasion, and metastasis^[60]24–[61]27. For instance,
   previous study has shown that the higher acetylation level of LDHA
   enhances the proliferation and metastasis of head and neck squamous
   carcinoma^[62]24. In HCC, LDHA was found to interact with FOXK2-142aa
   and activate its phosphorylation^[63]28. Notably, no investigations
   have focused on the regulatory mechanisms of HCC energy metabolism by
   CCDC91 and LDHA.

   In the present study, we investigated the role of the HBV integrated
   gene CCDC91 in HCC. Our results revealed that CCDC91 promoted HCC
   growth, metastasis, and resistance to sorafenib by enhancing aerobic
   glycolysis. These findings suggest that CCDC91 may serve as a novel
   molecular target for HCC intervention.

Methods

Patients and samples

   Paraffin-embedded of four HCC tissues were obtained from the First
   Affiliated Hospital of the University of Science and Technology of
   China (USTC) for HBV capture sequencing between June 2019 and January
   2021. All included HCC samples were positive for HBV serum markers and
   negative for the spirochete that causes syphilis and for other viruses,
   such as hepatitis C virus and human immunodeficiency virus. The
   clinicopathologic features of the patients are shown in Table [64]S1.
   The study was approved by the institutional ethics review committee of
   the First Affiliated Hospital of USTC and conducted according to the
   principles of the Declaration of Helsinki. The ethics committee waived
   the need for written informed consent because the study was conducted
   using residual samples from previous clinical diagnoses, the risks of
   the study did not exceed minimal risks, and the waiver of informed
   consent would not adversely affect the subjects. All ethical
   regulations relevant to human research participants were followed.

HBV capture sequencing

   HBV capture sequencing was conducted by MyGenostics (Beijing, China).
   The detailed experimental procedure has been previously
   described^[65]29. Briefly, DNA from paraffin-embedded HCC tissues was
   extracted and prepared for sequencing. The capture sequencing targeted
   HBV DNA to identify integration sites within the host genome. The
   integration sites were identified via Clipping Reveals Structure
   (CREST) analysis. HBV breakpoints with a supporting read number ≥2 were
   regarded with high confidence as HBV integration sites. The University
   of California Santa Cruz (UCSC) Genome Browser (GRCh37/hg19) was
   employed to annotate genes near the breakpoints.

Tissue microarray (TMA) and immunohistochemistry (IHC)

   This study included 123 HCC tumor tissues (all pathologically
   confirmed) for immunohistochemical staining, derived from two sources:
   80 matched pairs of tumor and corresponding paratumor tissues (i.e., 80
   tumor + 80 paratumor samples) and 43 additional non-matched HCC tumor
   tissues (without paired paratumor samples). Those tissues were obtained
   by the Shanghai National Engineering Research Center from Taizhou
   Hospital from 2010 to 2014 (approved by the Research Ethics Committee
   of Taizhou Hospital). All ethical regulations relevant to human
   research participants were followed. Comprehensive CCDC91 expression
   and survival analyses were performed on all 123 HCC cases. LDHA was
   specifically evaluated in 80 matched tumor pairs. In addition, the
   tumor tissues from the orthotopic xenografts and human HCC samples in
   this study were resected, fixed in 4% phosphate-paraformaldehyde (for
   at least 72 h), embedded in paraffin and sectioned at 5 μm. The IHC
   procedures included deparaffinization, rehydration, antigen retrieval,
   and blocking as reported previously^[66]30. Sections were incubated
   with primary antibodies at 4 °C overnight and then treated with
   secondary antibodies for 30 min at room temperature. The antibodies
   used for IHC targeted CCDC91 (1:200, sc-514452, Santa Cruz
   Biotechnology, Inc., U.S.A.), LDHA (1:200, 380954, Zenbio, Beijing,
   China), and ki-67 (1:200, 27309-1-AP, Proteintech, Rosemont, IL, USA).
   The intensity of the staining was evaluated as follows: negative (0
   points), weak (1 point), moderate (2 points), and strongly positive (3
   points). The percentage of positive tumor cells was scored as 0 (<5%),
   1 (<25%), 2 (25%-50%), 3 (51%-75%), and 4 (>75%). The final scores (0
   to 12) were based on the percentage of positive cells and the staining
   intensity.

Cell lines and cell cultures

   The human HCC cell lines SNU449, Huh-7, HepG2, and PLC/PRF/5, and
   normal liver cell line THLE-2 were obtained from the American Type
   Culture Collection (ATCC, United States). The cells were cultured in
   Dulbecco’s Modified Eagle Medium (DMEM) (Huh-7, HepG2, and PLC/PRF/5)
   or RPMI-1640 (SNU449) supplemented with 10% fetal bovine serum (FBS) in
   a humidified atmosphere of 5% CO[2] at 37  °C. Cell lines were
   authenticated by Biowing Applied Biotechnology Co., Ltd. (Shanghai,
   China), and short tandem repeat (STR) profiling was used to confirm
   their identity. For functional inhibition experiments, the indicated
   HCC cells were treated with sorafenib (Meilunbio, Dalian, China) at a
   final concentration of 8 μΜ^[67]31. The cells were incubated with
   sorafenib under the same culture conditions for the duration of the
   experiments.

Gene overexpression and knockdown

   Full-length cDNA encoding human CCDC91 was amplified via PCR and
   subsequently cloned and inserted into the
   pCDH-CMV-MCS-EF1-CopGFP-T2A-Puro lentiviral vector system. The primers
   used for constructing the CCDC91 overexpression vector were as follows:
   CCDC91-F: 5’- TGACCTCCATAGAAGATtctaga; and CCDC91-R:
   5’-gaattcGAATTTAAATCGGATCCG. The sequences of the short hairpin RNAs
   (shRNAs) used for CCDC91 knockdown were as follows: shCCDC91-1:
   5’-GAAGAGCAGAAACGAAGUGAATT; shCCDC91-2: 5’-UUCACUUCGUUUCUGCUCUUCTT.
   Plasmids for lentiviral packaging were transfected into 293 T cells
   with Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA). HCC cells
   grown at 60%-70% confluence were infected with the viral particle
   mixture. Short interfering RNA (siRNA) oligonucleotides targeting
   CCDC91 and LDHA were designed and synthesized by RiboBio (Guangzhou,
   China). The siRNA target sequences for CCDC91 were as follows:
   siCCDC91-1: 5’-CAACAUCUCCUGCUAUUCCUUTT and 5’-AAGGAAUAGCAGGAGAUGUUGTT;
   siCCDC91 -2: 5’-GAAGAGCAGAAACGAAGUGAATT and 5’-UUCACUUCGUUUCUGCUCUUCTT;
   and siCCDC91-3: 5’-GGCUCCUUGAAAUGCUAGAUATT and
   5’-UAUCUAGCAUUUCAAGGAGCCTT. The siRNA target sequences for LDHA were as
   follows: siLDHA-1: 5’-CCUUAGAACACCAAAGAUUTT and
   5’-AAUCUUUGGUGUUCUAAGGTT; siLDHA-2: 5’-GCACCCAGAUUUAGGGACUTT and
   5’-AGUCCCUAAAUCUGGGUGCTT; and siLDHA-3: 5’- GAUUACAGUUGUUGGGGUUTT and
   5’- AACCCCAACAACUGUAAUCTT. Furthermore, the 3-end deleted X genes
   (encoding HBx-180, Ct-HBx-180) were cloned and transduced into HepG2
   cells according to the manufacturer’s instructions. Transfection
   efficiency and gene expression levels were confirmed via qPCR and
   Western blot analysis.

CCK8 assay

   Cell proliferation was measured with a Cell Counting Kit-8 (CCK8,
   Dojindo, Kumamoto, Japan) according to the manufacturer’s instructions.
   Equal numbers of HCC cells were seeded into 96-well culture plates and
   incubated for 3–5 days. Incubate the 96-well plates for 2 h in the
   incubator and measure the absorbance at 450 nm using a microplate
   reader (Tecan, Switzerland). Each experiment was performed in
   triplicate.

Cell migration and invasion assays

   Cell migration or invasion was measured using Transwell inserts with an
   8 μm pore size culture membrane (Corning, Ithaca, NY, USA) covered
   without or with Matrigel (BD Biosciences, Franklin Lakes, NJ, USA)
   before use. For cell migration, equal numbers of HCC cells were
   resuspended in serum-free medium, and 200 μL of cell suspension was
   added to the upper compartment and incubated at 37  °C, with 700 μL of
   medium containing 10% FBS in the lower chamber. For cell invasion,
   cells in a 200 μL, serum-free culture medium was added to the
   compartment with a Matrigel-coated membrane diluted with serum-free
   culture medium. The cells were stained and counted after being cultured
   for 8-24 h.

Wound-healing assays

   For the cell motility assay, cells were seeded in 12-well plates to
   reach 90%-95% confluence. A single scratch wound was created with a
   20 μL pipette tip. The cell debris was removed by washing with PBS and
   replaced with culture medium. The samples were immediately photographed
   at a suitable time after wounding.

Animal experiments

   To construct a subcutaneous HCC model, CCDC91-overexpresion and
   -knockdown and control HCC cells (3 × 10^6) were injected into the
   right flanks of five-week-old male BALB/c nude mice (n = 5 per group).
   Sample sizes for animal studies were determined based on established
   laboratory experience with this xenograft model, with n = 5 mice per
   group providing consistent detection of biologically significant
   effects in prior experiments. All health mice were sourced from
   Shanghai SLAC Laboratory Animal Co. Ltd and randomly allocated to
   groups using the drawing lots. Cage location and order of procedures
   were balanced across groups to minimize environmental bias. All animals
   were maintained in specific-pathogen-free conditions. The tumor was
   excised prior to reaching a maximum volume of 2000 mm³. Tumor volumes
   were measured at the indicated time intervals, and the primary tumors
   were collected and weighed.

   To determine the antitumor effect of combined treatment with shCCDC91
   and sorafenib, CCDC91 -knockdown and control HCC cells were injected
   subcutaneously into the right flank of nude mice. The mice were
   randomly assigned to receive either sorafenib or control treatment
   (n = 5 per group). Vehicle and sorafenib (20 mg/kg/d) were given
   intraperitoneally five days per week. Tumor volumes were measured at
   the indicated time intervals. On day 28 of sorafenib treatment, the
   mice were sacrificed by cervical dislocation under deep anesthesia with
   CO2, and the primary tumors were collected and weighed.

   All experiments involving mice were approved by the Animal Care and Use
   Committees of the First Affiliated Hospital of USTC, and were performed
   in accordance with the Institutional Animal Welfare Guidelines. We have
   complied with all relevant ethical regulations for animal use.

Co-immunoprecipitation

   The co-immunoprecipitation (co-IP) experiments were performed on HepG2
   and PLC/PRF/5 cells via the Pierce^® Classic Magnetic IP/Co-IP Kit
   (Thermo Fisher, Waltham, MA, USA). Briefly, the cells were harvested
   using IP lysis buffer and lysed for 5 min. To reduce nonspecific
   binding, the total lysate was incubated with 25 μl of Pierce Protein
   A/G Magnetic Beads for 1 h. Primary antibody (anti-CCDC91,
   sc-514452,1:200, Santa Cruz Biotechnology; anti-LDHA,1:200, 380954,
   Zenbio; anti-HBx antibody,1:200, bs-2147R, Bioss, Beijing, China) was
   added at 4 °C overnight. The supernatant was then subjected to Western
   blot analysis.

Immunofluorescent confocal imaging

   Cells cultured on coverslips were fixed with 4% paraformaldehyde for
   20 min and permeabilized with 0.2% Triton X-100 for 10 min. After being
   washed 3 times with PBS, the cells were blocked with 5% BSA for 30 min
   and incubated with primary antibodies at 4 °C overnight. The glass
   slides were subsequently incubated with secondary antibodies
   (anti-CCDC91, Santa Cruz Biotechnology, 1:100, sc-514452; anti-HBx,
   1:200, 22741, Genetex, Alton Pkwy Irvine, CA, USA; anti-LDHA, 380954,
   Zenbio, 1:200) for 30 min in the dark. For nuclear staining, cells were
   incubated with DAPI (4’,6-diamidino-2-phenylindole; Servicebio, Wuhan,
   China) at a concentration of 5 μg/ml for 15 min at room temperature.
   Images of the cells were captured with a Leica TCS SP8 confocal system.

Glucose and lactate assays

   A glucose assay kit (Beyotime, Shanghai, China) and a lactate assay kit
   (Solarbio, Beijing, China) were used to determine glucose uptake and
   lactate production, respectively, according to the manufacturer’s
   protocols. For the glucose uptake colorimetric assay, cells were seeded
   at a density of 5 × 10^6 cells per well in a 6-well plate and starved
   by preincubating with 100 μL of Cell and Tissue Lysis Buffer
   (Beyotime). Dilute the Glucose standard (200 mg/ml) provided in this
   kit with distilled water to the required concentrations for the
   standard curve: 0, 5, 10, 20, 50, and 100 mg/dl. Add 5 μL of sample or
   standard to 96-well PCR plates and then add Glucose Assay Reagent
   (Beyotime) to a final volume of 190 μL. Mix by vortex and centrifuge
   briefly and place the tubes in a thermal cycler. Heat at 95 °C for
   8 min and then cool down to 4  °C. For the lactate assay, 5 × 10^6
   cells were homogenized in 100 μL of the assay buffer provided by the
   lactate assay kit, followed by centrifugation, and the supernatant was
   analyzed. The lactate standard (100 μmol/mL) provided in this kit with
   distilled water to the required concentrations for the standard curve:
   0, 0.078, 0.15625, 0.3125, 0.625, 1.25, and 2.5 mg/dl. Absorbance was
   measured at 630 nm for the glucose assay and 570 nm for the lactate
   assay. For both assays, the protein concentration of the cells was
   measured to normalize the glucose and lactate levels.

Western blot

   To analyze gene expression at the protein level, the cells were lysed
   in cold Radioimmunoprecipitation Assay (RIPA) buffer freshly
   supplemented with 1 mM phenylmethylsulfonyl fluoride (PMSF). The
   protein concentrations were measured with a Pierce BCA protein assay
   kit (Thermo Fisher). The quantification of proteins was performed to
   ensure consistent analysis, with 30 µg of total protein loaded per lane
   for subsequent Western blotting. Whole-cell protein lysates were
   separated by SDS‒PAGE and then transferred to a PVDF membrane. The
   membrane was blocked with 5% nonfat milk and then incubated with one of
   the following primary antibodies: anti-CCDC91 (1:1000, Abcam, ab227558,
   Cambridge, MA, USA), anti-HBx (1:500, Genetex, 22741), or anti-LDHA
   (1:1000, Zenbio (380954 and R380954)). Equal protein sample loading was
   confirmed via an anti-β-actin antibody (1:5000, 66009-1-Ig,
   Proteintech). All procedures strictly followed the kit manufacturer’s
   protocol.

Quantitative real-time PCR (qPCR)

   To detect gene expression at the mRNA level, total RNA samples were
   isolated from the HCC cell lines in this study with TRIzol reagent
   (Thermo Fisher) according to the manufacturer’s protocol. We used a
   FastStart Universal SYBR Green kit (Roche, Indianapolis, IN,
   Switzerland) on StepOne Plus Real-Time PCR System (Applied Biosystems)
   to preform quantitative real-time PCR (qPCR). Gene-specific primers
   were used at a final concentration of 10 µM each. The primers used are
   listed in Table [68]S2. qPCR was performed using the following cycling
   conditions: initial denaturation at 95 °C for 30 s; 40 cycles of
   denaturation at 95 °C for 5 s and annealing/extension at 60 °C for
   30 seconds with fluorescence acquisition; melting curve analysis from
   60 to 95 °C with 0.5  °C increments; and hold at 4  °C. The relative
   expression of the target genes was normalized to that of β-actin.

RNA-seq and bioinformatics analysis

   RNA-seq library preparation and sequencing of CCDC91-overexpressing and
   control HepG2 cells were performed on an Illumina NovaSeq 6000
   platform. Clean reads were aligned to the human genome hg38. The
   expression of the transcript was calculated by fragments per kilobase
   of exon model per million mapped reads (FPKM) using Perl. The filter
   criteria of p ≤ 0.05 and a fold change ≥2 were used to determine the
   differential expression of genes. We used a web-accessible functional
   annotation tool from the Database for Annotation, Visualization, and
   Integrated Discovery (DAVID) version 6.8
   ([69]https://david.abcc.ncifcrf.gov) to analyze the gene ontology (GO)
   and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment
   for differentially expressed genes. The transcript profiles from this
   study were uploaded to the NCBI database under accession number
   PRJNA1138405.

Public database

   The mRNA expression of CCDC91 in HCC tissues compared with noncancerous
   tissues was analyzed using data from The Cancer Genome Atlas (TCGA,
   [70]http://cancergenome.nih.gov) and the Gene Expression Omnibus (GEO,
   https:// [71]www.ncbi.nlm.nih.gov/geo/). Gene set enrichment analysis
   (GSEA) is a computational approach to determine if a pre-defined gene
   set can show a significant consistent difference between two biological
   states. We use the local version of the GSEA analysis tool
   [72]http://www.broadinstitute.org/gsea/index.jsp, Hallmark data set
   were used for GSEA independently. The overall survival (OS) curves of
   HCC patients from the TCGA dataset were generated by the online
   survival analysis tool Kaplan‒Meier plotter
   ([73]http://kmplot.com/analysis/). The CCDC91 high expression and low
   expression groups were classified using the “Auto select best cutoff”
   function. Survival curves were calculated using the Kaplan–Meier method
   and analyzed with a log-rank Mantel‒Cox test.

Statistics and reproducibility

   The significance of differences between groups was assessed with a
   Student’s t test (for normally distributed variables) or a Wilcoxon
   rank sum test (for nonnormally distributed variables). The experiments
   were conducted in triplicate. The results of the statistical analyses
   are presented as the mean ± standard error of the mean (SEM).
   Correlations between CCDC91 or LDHA expression levels and
   clinicopathological features were analyzed via multivariate logistic
   regression models. The independent effects of CCDC91 or LDHA expression
   on OS or progression-free survival were evaluated using multivariate
   Cox regression models from the TCGA dataset and our IHC cohort dataset.
   The level of significance was set at 0.05 for all the analyses.
   Statistical analyses were performed using SPSS software version 22.0
   (SPSS Inc., United States) or GraphPad Prism (GraphPad Software, United
   States).

Reporting summary

   Further information on research design is available in the [74]Nature
   Portfolio Reporting Summary linked to this article.

Results

CCDC91 is upregulated in HCC tissues and is correlated with a poor prognosis

   Our previous research revealed that the gene CCDC91 was recurrently
   inserted by HBV DNA in HCC (n = 16) and NHL (n = 1) samples
   (Fig. [75]1A). Recurrent insertion was identified using pooled analysis
   and HBV capture sequencing, respectively, suggesting that CCDC91 may
   share some common mechanisms in driving cancer initiation and
   progression. In this study, we further obtained HBV capture sequencing
   data from four HCC patients positive for HBV serum markers. A total of
   454 viral‒host junctions were identified in those tissues
   (Supplementary Data [76]2). Interesting, we found that CCDC91 (with a
   distance of ~100 kb) was inserted by HBV DNA once in HCC tissue A-2
   (Fig. [77]1A and Supplementary Data [78]2). Thus, a total of 17 HCC
   samples were identified with HBV integration around CCDC91
   (Supplementary Data [79]3). Moreover, the protein level of CCDC91 in
   tissue A-2 was much greater than that in the other three HCC tissues
   (Fig. [80]1B), suggesting that HBV DNA integration may induce CCDC91
   expression in HCC tissues.

Fig. 1. CCDC91 is upregulated in HCC tissues and is correlated with a poor
prognosis.

   [81]Fig. 1
   [82]Open in a new tab

   A Map of the CCDC91 gene with HBV DNA insertion in HCC (n = 17) and NHL
   (n = 1) tissues. Black arrows indicate HBV integration sites identified
   through pooled-analysis in HCC. Red arrows represent HBV integration
   sites detected in HCC samples using our HBV capture sequencing
   approach. Blue arrows denote HBV integration sites identified in
   non-Hodgkin lymphoma (NHL) samples from our previous HBV capture
   sequencing study. B Immunohistochemistry staining showed the protein
   expression of CCDC91 in 4 HBV capture sequencing HCC tissues. C The
   mRNA levels of CCDC91 in HCC tissues and non-cancerous liver tissues
   from GSEA cohorts ([83]GSE36376: n = 193 in non-tumor, n = 240 in
   tumor; [84]GSE76427: n = 52 in non-tumor, n = 115 in tumor). D The mRNA
   levels of CCDC91 in HCC tissues and non-cancerous liver tissues from
   TCGA cohort (n = 50 in non-tumor, n = 371 in tumor). E Relative mRNA
   levels of CCDC91 in HCC cells as determined by qPCR (n = 3 independent
   biological repeats). F Representative IHC images of CCDC91 in HCC
   tissues and adjacent paratumor tissues (left) and IHC scores of CCDC91
   staining in HCC tissues and non-cancerous liver tissues (right,
   n = 123). G The Kaplan–Meier analysis and log-rank test revealed the
   association of CCDC91 with the overall survival of HCC patients from
   TCGA dataset. H Multivariate logistic regression analyses for the
   associations of CCDC91 expression in HCC patients from TCGA dataset
   (n = 240). I Multivariate Cox regression analysis of the data from the
   TCGA dataset revealed that CCDC91 was an independent predictor of OS
   (n = 120). J The Kaplan–Meier analysis and log-rank test revealed the
   association of CCDC91 with the overall survival of HCC patients from
   TMA cohort (n = 123). K Multivariate logistic regression analyses for
   the associations of CCDC91 expression in HCC patients from TMA cohort
   (n = 80). Statistical analysis was performed using Student’s t test in
   (C, D, E, and F). Error bars represent the SEM. *, p < 0.05; **,
   p < 0.01; ***, p < 0.001.

   To determine the expression level of CCDC91 in HCC, we first analyzed
   data retrieved from the TCGA database, as well as microarray-based gene
   expression profiles ([85]GSE36376 and [86]GSE76427) from the GEO
   database (Fig. [87]1C, [88]D). The results revealed that the CCDC91
   mRNA level in HCC tissues was much higher than that in noncancerous
   liver tissues (p < 0.05, Fig. [89]1C, [90]D). We also investigated the
   expression of CCDC91 in a panel of human HCC cell lines. CCDC91
   expression was higher at the mRNA level (p < 0.05, Fig. [91]1E) in the
   4 HCC cell lines. The protein expression of CCDC91 was subsequently
   examined in parallel via immunohistochemical staining of the TMA
   cohort. Consistently, the protein level of CCDC91 was markedly
   increased in HCC tissues compared with noncancerous tissues (p < 0.01,
   Fig. [92]1F).

   To further explore the clinicopathological role of CCDC91 in HCC
   progression, we then analyzed data retrieved from the TCGA database and
   the Kaplan‒Meier survival analysis revealed that HCC patients with
   higher CCDC91 mRNA levels had shorter OS times than did patients with
   lower CCDC91 levels (p < 0.001, Fig. [93]1G). Multivariate logistic
   regression analyses for the TCGA cohort revealed that the CCDC91 mRNA
   level was positively correlated with TNM (tumor, lymph node, and
   metastasis) stage (p < 0.05, Fig. [94]1H and Table [95]S3).
   Additionally, multivariate Cox regression analyses indicated that
   CCDC91 expression was an independent predictor of HCC aggressiveness
   (p < 0.05, Fig. [96]1I and Table [97]S4). Based on our TMA cohort data,
   we also found that HCC patients with high CCDC91 protein expression had
   a significantly shorter OS time (p < 0.001, Fig. [98]1J).
   Interestingly, further multivariate logistic regression analysis
   revealed that CCDC91 expression in HCC tissues was positively
   associated with HBV DNA status (p < 0.05, Fig. [99]1K and
   Table [100]S5). Collectively, these data suggest that CCDC91 plays a
   crucial role in HCC.

CCDC91 promotes the malignant behavior of HCC in vitro and in vivo

   To investigate the functional role of CCDC91 in HCC, we chose HepG2 and
   PLC/PRF/5 cells for overexpression studies because they exhibit
   relatively low intrinsic expression of CCDC91, allowing us to more
   clearly observe the functional effects of CCDC91 upregulation. qPCR and
   Western blot confirmed the successful induction of CCDC91
   overexpression in HCC cells (Fig. [101]2A, [102]B). CCDC91
   overexpression significantly increased the proliferation (p < 0.011;
   Fig. [103]2C), migration (p < 0.05; Fig. [104]2D–F), and invasion
   abilities (p < 0.01; Fig. [105]2G) of HepG2 and PLC/PRF/5 cells.
   Conversely, we selected Huh-7 and SNU449 cells for knockdown
   experiments due to their relatively high endogenous expression of
   CCDC91, which provides a robust model for studying the loss-of-function
   effects (Fig. [106]S1). In contrast, knocking down CCDC91 significantly
   inhibited the proliferation, migration, and invasion of HCC cells
   (p < 0.05; Fig. [107]2H–L and Fig. [108]S2).

Fig. 2. CCDC91 promotes cell proliferation, migration, and invasion in vitro
in HCC cells.

   [109]Fig. 2
   [110]Open in a new tab

   A The mRNA level of CCDC91 in CCDC91-overexpressing HCC cells and
   control cells revealed by qPCR (n = 3). B The protein level of CCDC91
   in CCDC91-overexpressing HCC cells and control cells detected by
   western blot. C Cell proliferation of CCDC91-overexpressing HCC cells
   and control cells detected by CCK8 assay (n = 3). D, E The migration
   abilities of CCDC91-overexpressing HCC cells and control cells measured
   by wound healing assay (n = 3). The migration (F) and invasion (G)
   abilities of CCDC91-overexpressing HCC cells and control cells measured
   by transwell assay (n = 3). H Cell proliferation of CCDC91 knockdown
   HCC cells and control cells detected by CCK8 assay (n = 3). I, J The
   migration abilities of CCDC91 knockdown HCC cells and control cells
   measured by wound healing assay (n = 3). K, L The migration and
   invasion abilities of CCDC91 knockdown HCC cells and control cells
   measured by transwell assay (n = 3). Statistical analysis was performed
   using Student’s t test in (A, C, E, F, G, H, J, and L). Data represents
   mean ± SEM. *, p < 0.05; **, p < 0.01; ***, p < 0.001.

   To investigate the in vivo role of CCDC91, Huh-7 cells infected with
   shCCDC91 or controls were subcutaneously inoculated into athymic nude
   mice and the growth of the tumors was monitored. Compared with control
   tumors, tumors derived from Huh-7-shCCDC91 cells grew significantly
   slower (p < 0.01; Fig. [111]3A). At 36 d postinoculation, consistent
   with the results of tumor growth, a significant decrease in tumor
   weight was observed in the CCDC91 knockdown group compared with the
   control group (0.656 ± 0.091 g vs. 0.466 ± 0.130 g, p < 0.05,
   Fig. [112]3B, [113]C). Meanwhile, we also conducted in vivo experiments
   using subcutaneous mouse models of CCDC91 overexpressing HepG2 cells.
   Consistent with our CCDC91 knockdown findings in vivo, CCDC91
   overexpression significantly increased the tumor burden in subcutaneous
   (0.133 ± 0.057 g vs. 0.377 ± 0.063 g, p < 0.05, Fig. [114]3D, [115]E)
   mouse models of HCC. Ki-67 staining indicated that CCDC91 promoted cell
   growth (p < 0.01; Fig. [116]3F, [117]G). Collectively, these findings
   suggest that CCDC91 plays a critical role in promoting the malignant
   behavior of HCC in vitro and in vivo.

Fig. 3. CCDC91 promotes cell proliferation in vivo.

   [118]Fig. 3
   [119]Open in a new tab

   A–C The subcutaneous tumor model formed by Huh-7-shCCDC91 and control
   Huh-7-SC cells in BALB/c nude mice (n = 5 per group). A The tumor
   growth curves based on tumor sizes measured at a 5-day interval. B
   Representative images of tumors at the time of sacrifice 36 days post
   tumor cells inoculation. C The tumor weights at the time of sacrifice.
   D, E The subcutaneous tumor model formed by HepG2-CCDC91 and control
   HepG2-VC cells in BALB/c nude mice. Representative images were shown
   (D) and the tumors with xenografts were weighted (E) (n = 5,
   respectively). F Representative images of IHC staining of CCDC91 and
   Ki-67 in the HCC tumors. G Quantification of the percentage of
   Ki-67-positive cells and CCDC91-positive cells. Statistical analysis
   was performed using Student’s t test in (C, E, and G). Two-way ANOVA
   was used for tumor volume in (A). Data represents mean ± SEM.*,
   p < 0.05; **, p < 0.01; ***, p < 0.001.

CCDC91 exerts its protumor effects via the aerobic glycolysis pathway

   GSEA of the TCGA datasets was used to identify the molecular pathways
   that were significantly associated with CCDC91 expression. HCC patients
   were classified into two groups according to the mRNA expression level
   of CCDC91. The GSEA indicated that CCDC91 was associated mostly with
   genes involved in glycolysis (NES = 2.28, p < 0.001, Fig. [120]4A and
   Supplementary Data [121]4). Additionally, we compared the whole genome
   mRNA expression profiles of HepG2-VC and HepG2-CCDC91 cells using
   RNA-seq. A distinct transcriptome difference was observed
   (Fig. [122]4B) with 2625 genes significantly upregulated and 4033 genes
   downregulated by CCDC91 overexpression (|log2FC | ≥ 1, p ≤ 0.05). KEGG
   pathway enrichment analysis of the upregulated genes revealed that the
   glycolysis signaling pathway was also significantly enriched (p < 0.05,
   Fig. [123]4C).

Fig. 4. CCDC91 exerts its pro-tumor function via the LDHA-related aerobic
glycolysis pathway.

   [124]Fig. 4
   [125]Open in a new tab

   A Upregulation of CCDC91 expression was positively correlated with
   activated glycolysis metabolic pathways in HCC as predicted by GSEA
   from TCGA dataset (GSEA, gene set enrichment analysis; NES, normalized
   enrichment score, p < 0.001). B The volcano graph showing the
   differentially expression genes (DEGs; |log2FC | ≥ 1, p ≤ 0.05)
   identified by RNA-seq between HepG2-CCDC91 and HepG2-VC cells. C The
   top 20 pathways revealed by KEGG enrichment analysis of DEGs. D Glucose
   levels were detected in CCDC91-overexpressing HCC cells and control
   cells (n = 3). E Lactate levels were detected in CCDC91-overexpressing
   HCC cells and control cells (n = 3). F The mRNA level of the key
   glycolysis differential expressed genes in CCDC91-overexpressing HCC
   cells and control cells by qPCR (n = 3). G The protein level of LDHA in
   CCDC91-overexpressing HCC cells and control cells by western blot
   (n = 3). H Correlation analysis of CCDC91 and LDHA levels in HCC
   tissues using the data from TCGA database. I Immunohistochemistry
   staining and analysis showed the protein expression of LDHA in HCC
   tissues and matched non-cancerous liver tissues (n = 80). J The
   Kaplan–Meier analysis revealed the association of LDHA with the overall
   survival of HCC patients from TMA cohort (n = 80). K Correlation
   analysis of CCDC91 and LDHA levels in HCC tissues using the data from
   TMA cohort (n = 80). Statistical analysis was performed using Student’s
   t test in (D, E, F, and I). Data represents mean ± SEM. *, p < 0.05;
   **, p < 0.01; ***, p < 0.001.

   We then investigated the potential role of aerobic glycolysis in the
   development of HCC following CCDC91 overexpression by examining the
   regulatory effects of CCDC91 on glucose uptake and lactate production.
   As anticipated, overexpression of CCDC91 resulted in increased lactate
   production in HepG2 and PLC/PRF/5 cell lines (p < 0.001, Fig. [126]4D,
   [127]E). We also performed qPCR on key glycolysis-related genes,
   including GLUT1, HK2, MCT-1, MCT2, and LDHA, which were identified as
   differentially expressed in CCDC91-overexpressing cells via RNA-seq.
   The mRNA expression of LDHA was significantly greater in
   CCDC91-overexpressing cells than in control cells (p < 0.05,
   Fig. [128]4F). Western blot analysis also confirmed the increased
   protein expression of LDHA following CCDC91 overexpression
   (Fig. [129]4G). LDHA, a key enzyme in the glycolytic pathway, is highly
   expressed in various cancers. Clinical analysis of TCGA data clearly
   revealed that LDHA mRNA levels were positively correlated with CCDC91
   levels (p < 0.001, R = 0.44; Fig. [130]4H). Consistent with previous
   studies^[131]32, in a TMA containing 80 HCC tissues, we found the
   expression of LDHA was markedly increased in HCC tissues compared with
   noncancerous tissues (p < 0.05, Fig. [132]4I). Moreover, we found that
   HCC patients with higher LDHA protein levels had a shorter OS time than
   did patients with lower levels of LDHA (p < 0.05, Fig. [133]4J).
   Interestingly, multivariate logistic regression analysis indicated a
   borderline significant positive association between LDHA expression and
   HBV DNA status in HCC tissues (p = 0.059, Table [134]S6). Additionally,
   a significant correlation between LDHA and CCDC91 was confirmed
   (p < 0.001, R = 0.65; Fig. [135]4K) for protein levels. Collectively,
   these results indicate that CCDC91 and LDHA may be key regulatory
   factors involved in the HBV-related HCC and exert their effects through
   the glycolytic pathway.

LDHA is a downstream target of CCDC91 in CCDC91-overexpressing cells

   Following the biosignature analysis that indicated that CCDC91
   influenced glycolysis through LDHA, we investigated the potential
   interaction between the two proteins. As shown in Fig. [136]5A, co-IP
   demonstrated that CCDC91 and LDHA could interact with each other in
   PLC/PRF/5 and HepG2 cells. Additionally, immunofluorescence staining
   confirmed the significant colocalization of CCDC91 and LDHA in the
   cytoplasm of HCC cells (Fig. [137]5B). Notably, the immunofluorescence
   signals for both CCDC91 and LDHA were stronger in the
   CCDC91-overexpressing group than in the control group (Fig. [138]5B).

Fig. 5. LDHA mediates CCDC91-induced cell proliferation, migration, and
invasion in HCC cells.

   [139]Fig. 5
   [140]Open in a new tab

   A Co-IP with antibody against CCDC91 followed by Western blot in HepG2
   and PLC/PRF/5 cells (n = 3). B Immunofluorescence staining of CCDC91
   and LDHA in CCDC91-overexpressing HCC cells and control cells. C The
   mRNA level of LDHA in CCDC91-overexpressing HCC cells with or without
   LDHA knockdown revealed by qPCR (n = 3). D The protein level of LDHA in
   CCDC91-overexpressing HCC cells with or without LDHA knockdown detected
   by western blot (n = 3). E Cell proliferation of CCDC91-overexpressing
   HCC cells with or without LDHA knockdown detected by CCK8 assay
   (n = 3). (F–I). F, G The migration abilities of CCDC91-overexpressing
   HCC cells with or without LDHA knockdown measured by transwell assay
   (n = 3). The migration (H, I) and invasion (J, K) abilities of
   CCDC91-overexpressing HCC cells with or without LDHA knockdown measured
   by wound healing and transwell assay, respectively (n = 3). L Glucose
   levels were detected in CCDC91-overexpressing HCC cells with or without
   LDHA knockdown (n = 3). M Lactate levels were detected in
   CCDC91-overexpressing HCC cells with or without LDHA knockdown (n = 3).
   Statistical analysis was performed using Student’s t test in (C, E, G,
   I, K, L, and M). Data represents mean ± SEM. *, p < 0.05; **, p < 0.01;
   ***, p < 0.001.

   To elucidate the biological function of LDHA in HCC, we transfected
   CCDC91-overexpressing cells with LDHA-siRNA and subsequently analyzed
   cell growth, migration, and invasion. qPCR and Western blot confirmed
   the successful reduction in LDHA in PLC/PRF/5 and HepG2 cells
   (p < 0.05, Fig. [141]5C, [142]D). CCDC91 overexpression increased the
   proliferative, migratory, and invasive abilities of HCC cells, which
   were decreased by LDHA knockdown (p < 0.05, Fig. [143]5E–K). Moreover,
   LDHA knockdown weakened the capability of lactate production induced by
   CCDC91 in HCC cells (p < 0.01, Fig. [144]5L, [145]M). In summary, these
   findings collectively suggest that CCDC91 promotes glycolysis by
   increasing LDHA expression in HCC.

CCDC91 deficiency confers sensitivity to sorafenib in HCC cell lines

   Sorafenib, a multikinase inhibitor, is approved as the standard therapy
   for advanced HCC patients but provides only limited survival benefits,
   particularly for Asia–Pacific patients. Given that glycolysis signaling
   is implicated in a poor response to sorafenib^[146]33, we explored the
   effect of CCDC91 on sorafenib sensitivity. Based on our TMA cohort, we
   observed that HCC patients with stronger CCDC91 expression had a
   significantly shorter survival than those with weak CCDC91 expression
   when they were treated with sorafenib (Fig. [147]6A, [148]B).
   Consistently, in PLC/PRF/5 cells, CCDC91 overexpression significantly
   counteracted the inhibitory effects of sorafenib on cell growth,
   migration, and invasion (p < 0.05, Fig. [149]6C–E). In HepG2 cells, a
   similar resistance phenotype was observed, with CCDC91 overexpression
   significantly diminishing sorafenib’s suppression of cell growth and
   migration (p < 0.05, Fig. [150]6C, D). However, for invasion, the
   effect was less pronounced, showing only a non-significant trend
   (Fig. [151]6E).

Fig. 6. Knockdown of CCDC91 confers sensitivity to sorafenib.

   [152]Fig. 6
   [153]Open in a new tab

   A The Kaplan–Meier analysis revealed the association of CCDC91 with the
   progression free survival of HCC patients that treated with sorafenib
   from TMA cohort (n = 77). B The Kaplan–Meier analysis revealed the
   association of CCDC91 with the overall survival of HCC patients that
   treated with sorafenib from TMA cohort (n = 80). C Cell proliferation
   of CCDC91-overexpressing HCC cells and control cells with or without
   sorafenib detected by CCK8 assay for 24 h, 48 h and 72 h separately
   (n = 3). The migration (D) and invasion (E) abilities of
   CCDC91-overexpressing HCC cells with or without sorafenib measured by
   transwell assay for 18 h (n = 3). F–H Huh-7 cells stably expressing SC
   or shCCDC91 were injected subcutaneously into the flanks of nude mice
   administrated without or with sorafenib (n = 5). Representative images
   of dissected tumors at the end of the experiment were shown. G Tumor
   growth curves of mice during sorafenib treatment were analyzed (n = 5).
   And xenografts were weighted (n = 5, H). All control cells were treated
   with an equivalent volume of DMSO to account for potential solvent
   effects, while the experimental groups were treated with sorafenib
   dissolved in DMSO. Statistical analysis was performed using Student’s t
   test in (C, D, E, and H). Two-way ANOVA was used for tumor volume in G
   Data represents mean ± SEM. *, p < 0.05; **, p < 0.01; ***, p < 0.001.

   To validate these findings in vivo, we employed a xenograft model. Our
   results revealed that either CCDC91 knockdown or sorafenib
   (20 mg/kg/day) alone inhibited tumor growth in vivo (Fig. [154]6F).
   Importantly, knockdown of CCDC91 expression in Huh-7 cells
   significantly increased the efficacy of tumor growth inhibition by
   sorafenib (p < 0.05, Fig. [155]6F–H). These results provide persuasive
   evidence that targeting CCDC91 signaling is an efficient strategy to
   increase the antitumor efficacy of sorafenib.

Ct-HBx mediates HBV integrated CCDC91 overexpression in HCC cells

   Previously, we found that HBV DNA integration in HCC tissues may induce
   CCDC91 overexpression. While the Ct-HBx is crucial in the pathogenic
   mechanism of HBV DNA integration, we wanted to explore the interaction
   between the Ct-HBx and CCDC91. We transfected PLC/PRF/5 and HepG2 cells
   with Ct-HBx plasmid. Western blot confirmed the successful
   overexpression in HBx in PLC/PRF/5 and HepG2 cells (p < 0.05,
   Fig. [156]7A). To first determine whether the expression of CCDC91 mRNA
   is regulated by the Ct-HBx, qPCR was performed to compare the CCDC91
   levels among the Ct-HBx infected cells as well as the control cells.
   The results revealed that CCDC91 was significantly upregulated in the
   Ct-HBx infected cells (p < 0.001, Fig. [157]7B), indicating that the
   Ct-HBx mediated CCDC91 overexpression and activation. To investigate
   the molecular mechanisms involved in regulating CCDC91 expression, we
   performed co-IP by transfecting the Ct-HBx plasmids into HepG2 and
   PLC/PRF/5 cells. As shown in Fig. [158]7C, co-IP demonstrated that HBx
   could bind to CCDC91. Additionally, immunofluorescence verified that
   CCDC91 and HBx significantly colocalized in the cytoplasm of HepG2 and
   PLC/PRF/5 cells (Fig. [159]7D), and when the cells were infected with
   the Ct-HBx plasmid, the immunofluorescence intensity of CCDC91 and HBx
   in the overexpression group was greater than that in the control group.
   Consistent with the function of CCDC91 overexpression in HCC,
   transfection of the Ct-HBx plasmid promoted the proliferation and
   metastasis of HepG2 and PLC/PRF/5 cells in vitro (p < 0.05,
   Fig. [160]7E–G). Moreover, by western blot we found that transfection
   of Ct-HBx promoted CCDC91-induced upregulation of LDHA (Fig. [161]7G)
   in HepG2 and PLC/PRF/5 cells.

Fig. 7. Ct-HBx mediates HBV integrated CCDC91 overexpression in HCC cells.

   [162]Fig. 7
   [163]Open in a new tab

   A The protein level of HBx in HepG2 and PLC/PRF/5 cells with or without
   Ct-HBx transfection detected by western blot (n = 3). B The mRNA level
   of CCDC91 in HepG2 cells with or without Ct-HBx transfection revealed
   by qPCR (n = 3). C Co-IP with antibody against HBx followed by Western
   blot in HepG2 and PLC/PRF/5 cells (n = 3). D Immunofluorescence
   staining of CCDC91 and HBx in HepG2 and PLC/PRF/5 cells with or without
   Ct-HBx transfection. E Cell proliferation of HepG2 and PLC/PRF/5 cells
   with or without Ct-HBx transfection detected by CCK8 assay (n = 3). F,
   G) The migration and invasion abilities of HepG2 and PLC/PRF/5 cells
   with or without Ct-HBx transfection measured by transwell assay
   (n = 3). H The protein level of HBx, CCDC91, and LDHA in HepG2 and
   PLC/PRF/5 cells with or without Ct-HBx transfection revealed by western
   blot (n = 3). I Schematic diagram illustrating the proposed mechanisms
   of the effects of the HBV-integrated gene CCDC91 on HCC. Statistical
   analysis was performed using Student’s t test in (B, E, F, and G). Data
   represents mean ± SEM.*, p < 0.05; **, p < 0.01; ***, p < 0.001.

   Overall, we propose that HBV DNA integration causes aberrant expression
   of CCDC91 in HCC, which leads to the activation of LDHA via the aerobic
   glycolysis pathway. CCDC91 deficiency also increased sensitivity to
   sorafenib treatment (Fig. [164]7H).

Discussion

   Increasingly researchers agree that HBV DNA integration plays a crucial
   role in hepatocarcinogenesis^[165]34. On the basis of a sizeable cohort
   of clinical HBV-related HCC cases analyzed through
   pooled-analysis^[166]35 and our recent HBV capture sequencing data, we
   identified preferential HBV–human chimeric fusions with breakpoints at
   the CCDC91 gene. Moreover, we found a trend that HBV integration at
   CCDC91 was associated with increased CCDC91 protein expression, and HCC
   patients with higher CCDC91 expression had poorer survival. To date,
   these findings represent the first demonstration of a relationship
   between HBV integration and CCDC91.

   The characterization of integrated HBV DNA segments in the host genome
   provides a better understanding of the pathogenic mechanism and role of
   HBV in HCC. Previous studies have shown that the integrated DNA of HBV
   in HCC usually contains the viral basal core promoter (BCP)/enhancer II
   (Enh II), and the sequence encoding the C-terminal truncated HBx which
   is a pleiotropic transactivator^[167]36. Recently, Zhang et al.
   reported that the Ct-HBx mediated metabolic reprogramming from
   mitochondrial respiration to aerobic glycolysis via the NFACT2-TXNIP
   signaling pathway, indicating that the Ct-HBx plays a critical role in
   hepatocarcinogenesis^[168]12. In addition, full-length HBx also has
   pleiotropic properties that support viral gene expression and
   replication and contribute significantly to HCC
   development^[169]23,[170]36. One study reported that HBx could interact
   with NF-κBp65 at both the transcriptional and protein levels,
   upregulate the NF-κBp65/HK2 axis and increase cell
   proliferation^[171]23. In this study, we found that HBx, which is
   induced by the Ct-HBx, could upregulate the CCDC91 in HepG2 cells. To
   investigate the molecular mechanisms involved in regulating CCDC91
   expression in HBV-related HCC, we performed co-IP and found that HBx
   and CCDC91 interacted with each other and enhanced cell proliferation,
   migration, and invasion in HepG2 cells. Whether Ct-HBx affects CCDC91
   in HCC cells at the transcriptional level requires further
   investigation.

   The detailed function and mechanism of CCDC91 in cancer development
   remain unclear. Previously, we reported that patients with high
   expression of CCDC91 had poor survival, with borderline significance,
   for NHL^[172]29. In addition to cancers, some genome-wide association
   studies have reported that CCDC91 polymorphisms may be associated with
   lung function^[173]37, ossification of the posterior longitudinal
   ligament^[174]38, and bone remodeling^[175]39. Recently, Zhu et al.
   revealed that the CCDC91 gene is a pathogenic gene involved in the
   development of acrokeratoelastoidosis by using linkage analysis and
   whole-exome sequencing. Additionally, the authors reported that the
   CCDC91 gene plays a crucial role in elastin transport^[176]40. In this
   study, based on the loss-of-function and gain-of-function studies,
   CCDC91 was shown to contribute to the proliferation and metastasis of
   HCC. To date, the role of CCDC91 in HCC had not been studied. Our
   functional findings were also supported by the clinical observation
   that HCC patients with high tumor expression of CCDC91 had a poorer TNM
   stage and poorer survival. More interestingly, multivariate logistic
   regression analysis revealed that CCDC91 expression in HCC tissues was
   positively associated with HBV DNA status. High copy numbers of HBV DNA
   in HCC patients have been associated with a poor prognosis^[177]41.
   These data suggest a vital role for CCDC91 in HBV-related HCC.
   Furthermore, we discovered that CCDC91 modulates aerobic glycolysis
   levels by interacting with LDHA, a metabolite that promotes tumor
   growth and metastasis in HCC. LDHA is one of the key regulators
   involved in glycolytic metabolism and is highly expressed in various
   tumors, such as head and neck squamous carcinoma^[178]24, colorectal
   cancer^[179]25, and HCC^[180]26,[181]28, and LDHA influences tumor
   proliferation, migration, and nuclear regulation. By performing an
   integrated analysis of data from HCC patients from the TCGA database
   and our RNA-sequencing data, we demonstrated that CCDC91 could
   upregulate the expression of LDHA. Moreover, the reduced proliferation,
   migration, and invasion ability induced by overexpression of CCDC91 in
   HCC cells was largely abolished by the introduction of siLDHA,
   indicating that therapeutic strategies that disrupt the interaction
   between CCDC91 and LDHA have the potential to prevent cancer growth and
   metastasis, especially in patients with high CCDC91 expression.

   Although HCC is a highly aggressive type that remains difficult to
   treat, efforts to exploit effective therapeutic approaches (such as
   immune checkpoint inhibitors^[182]42, antiangiogenic agents^[183]43,
   and CDK4/6 inhibitors^[184]44) for treating this disease are ongoing.
   Among these, the multikinase inhibitor sorafenib is an attractive
   therapeutic option. Sorafenib is the standard of care for the treatment
   of advanced HCC, but it is associated with the development of
   resistance^[185]45. Several factors including HIF-1α^[186]46,
   EGFR^[187]47, MEK signaling^[188]48, and aerobic glycolysis^[189]33
   limit the efficiency of sorafenib. Aerobic glycolysis is a major
   resistance mechanism induced by first-line treatment of HCC with
   sorafenib. In this study, HCC patients with stronger CCDC91 expression
   had significantly shorter survival than those with weak CCDC91
   expression when they treated with sorafenib. By performing an in vivo
   study, we also found that the knockdown of CCDC91 in HCC cells resulted
   in increased sensitivity to sorafenib. These data indicate that CCDC91
   may affect sorafenib sensitivity via aerobic glycolysis signaling,
   further investigation of this pathway might be useful for overcoming
   resistance to sorafenib in HCC.

   There are several limitations to our study. First, we detected only 4
   HBV-associated HCCs with HBV capture sequencing in this study. Most of
   the data on HBV DNA integration at the CCDC91 locus were obtained from
   our previous pooled-analyses. Therefore, the real pattern of HBV DNA
   integration at the CCDC91 locus awaits further larger-scale
   investigations. Second, combined with the corresponding in-vitro data,
   we highlight that the expression of CCDC91 may be induced by Ct-HBx and
   that HBx and CCDC91 bind with each other in HCC cells. However, we
   acknowledge that we did not provide direct in vitro evidence linking
   HBV DNA integration to CCDC91 upregulation. Further investigation is
   needed to fully understand the direct mechanism induced by the
   HBV-integrated sequence. Finally, understanding the detailed mechanism
   by which CCDC91 affects sorafenib sensitivity requires further study.

   Overall, our work revealed that HBV DNA integration caused aberrant
   expression of CCDC91 in HCC, which led to the activation of LDHA via
   the aerobic glycolysis pathway. Furthermore, CCDC91 deficiency
   increased sensitivity to sorafenib treatment. The results strongly
   demonstrated that CCDC91 could serve as a potential biomarker and
   promising therapeutic target in HBV-induced HCC.

Supplementary information

   [190]Supplementary Information^ (879.4KB, pdf)
   [191]42003_2025_8369_MOESM2_ESM.docx^ (14.9KB, docx)

   Description of Additional Supplementary Files
   [192]Supplementary Data 1^ (43.7KB, xlsx)
   [193]Supplementary Data 2-4.^ (40.2KB, xlsx)
   [194]Reporting Summary^ (1.8MB, pdf)

Acknowledgements