Abstract

   Background: Chemotherapy is the basic treatment for colorectal cancer
   (CRC). However, colorectal cancer cells often develop resistance to
   chemotherapy drugs, leading to recurrence and poor prognosis. More and
   more studies have shown that the Homologous recombination (HR) pathway
   plays an important role in chemotherapy treatment for tumors. However,
   the relationship between HR pathway, chemotherapy sensitivity, and the
   prognosis of CRC patients is still unclear.

   Methods: We collected 35 samples of CRC patients after chemotherapy
   treatment from Guangxi Medical University Cancer Hospital, then
   collected mutation data and clinical prognosis data from the group. We
   also downloaded Mondaca-CRC, TCGA-CRC cohorts for chemotherapy
   treatment.

   Result: We found that HR mutant-type (HR-MUT) patients are less likely
   to experience tumor metastasis after receiving chemotherapy.
   Additionally, our univariate and multivariate cox regression models
   showed that HR-MUT can be used as an independent predictor of the
   prognosis of chemotherapy for CRC patients. The KM curve showed that
   patients with HR-MUT CRC had significantly prolonged overall survival
   (OS) time (log-rank p = 0.017; hazard ratio (HR) = 0.69). Compared to
   HR mutant-type (HR-WT), HR-MUT has a significantly lower IC50 value
   with several chemotherapeutic drugs. Pathway enrichment analysis
   further revealed that the HR-MUT displayed a significantly lower rate
   of DNA damage repair ability, tumor growth, metastasis activity, and
   tumor fatty acid metabolism activity than HR-WT, though its immune
   response activity was notably higher.

   Conclusion: These findings indicate that HR-MUT may be a relevant
   marker for CRC patients receiving chemotherapy, as it is closely
   related to improving OS time and reducing chemotherapy resistance.

   Keywords: colorectal cancer, chemotherapy, biomarker, prognosis,
   homologous recombination

Introduction

   Colorectal cancer, or colon cancer, is one of the most common types of
   malignant tumors found in the human digestive tract and is a seriously
   threat to human health. Its incidence rate ranks third amongst that of
   all malignant tumors worldwide, and its mortality rate ranks second
   ([54]Miller et al., 2020; [55]Liu et al., 2022a; [56]Liu et al.,
   2022b). At present, besides surgery, chemotherapy is the main treatment
   for colon cancer. However, due to the high heterogeneity of colon
   cancer, the benefits of these treatments for difference patients may
   vary greatly. Moreover, the occurrence of chemotherapy resistance can
   result in failure of the final treatment of colon cancer patients
   ([57]Bian et al., 2016; [58]Fu et al., 2016). Therefore, it is of the
   utmost importance to investigate the specific mechanism of the
   occurrence and development of colon cancer and any accompanying
   chemotherapy resistance in order to develop new therapeutic targets,
   reverse chemotherapy resistance, and ultimately improve the prognosis
   of colon cancer patients.

   Recent studies have shown that the molecular mechanisms of chemotherapy
   resistance mainly involve: 1) The reduction of the activation of drug
   precursors and the concentration of drugs in cells through drug efflux
   and inactivation; 2) Changes in drug action targets; 3) Disturbance of
   cell survival and apoptosis; 4) Hypoxia in the tumor microenvironment;
   5) Changes in the extracellular mechanism; 5) Cytokines and other
   growth factors that maintain the activation of tumor survival-related
   pathways ([59]Li et al., 2017).

   Homologous recombination (HR) is a stable and error-free repair process
   that uses homologous sister chromatids as a template. HR determines the
   survival and fate of cells ([60]Gonzalez and Stenzinger, 2021; [61]Liu
   et al., 2021). Still, despite its reliability, the main cause of DNA
   damage in the S/G2 cell cycle is HR ([62]Lisby and Rothstein, 2015). HR
   plays an important role in repairing cisplatin adducts, a DNA repair
   process that plays an important role in the chemotherapy resistance of
   tumor cells ([63]Zdraveski et al., 2000). For example, HR-deficient
   Escherichia coli strains are known to show higher sensitivity to
   chemotherapeutic drugs than Nucleotide excision repair (NER)-deficient
   Escherichia coli strains ([64]Zdraveski et al., 2000), while homologous
   recombination defect (HRD) is known to be related to chemotherapy
   resistance in ovarian cancer patients ([65]Xiao et al., 2017). However,
   at present, the relationship between the mutation state of the HR
   pathway and the chemotherapy efficacy, prognosis, and chemotherapy
   sensitivity of CRC patients is unclear.

   In this study, we use data collected from a sample of CRC patients who
   have been treated with chemotherapy from Guangxi Medical University
   Cancer Hospital to explore the relationship between the mutation state
   of HR pathway and the prognosis of the chemotherapy efficacy of CRC
   patients through curative effect analysis, prognosis analysis, and drug
   sensitivity analysis. Through this process, we found that HR-MUT CRC
   patients had significantly prolonged survival time and higher
   sensitivity to chemotherapy drugs. Therefore, HR-MUT may be a useful
   predictive marker for CRC patients receiving chemotherapy in future
   treatments.

Materials and Methods

CRC Cohort Collection

   This study includes samples of primary CRC patients that underwent
   colon cancer resection and chemotherapy in Guangxi Medical University
   Cancer Hospital between 2015 to 2021. The sample patients were divided
   into patients with tumor metastasis and without tumor metastasis. We
   obtained the mutation data by targeted sequencing. We also collected
   the clinical data of the 35 patients, including their level of
   metastasis, sex, TNM stage, Eastern Cooperative Oncology Group
   Performance Status (ECOG), age, height, and weight. All participants
   signed a written informed consent agreement, and the work was approved
   by the Research Ethics Committee of Guangxi Medical University Cancer
   Hospital.

   To expand our data, we downloaded a CRC cohort for chemotherapy
   (Mondaca-CRC;
   [66]https://www.cbioportal.org/study/clinicalData?id=crc_apc_impact_202
   0) from the cbioportal web tool ([67]Mondaca et al., 2020), as well as
   the entirety of the exon sequencing data and clinical data (including
   Tumor mutational burden (TMB), Microsatellite instability (MSI) scores,
   MSI status, gender, TNM stage, ECOG and age). We downloaded the RNA
   sequencing data, mutation data, and clinical prognosis data of
   TCGA-COAD and TCGA-READ from TCGA database
   ([68]https://portal.gdc.cancer.gov/) using TCGAbiolinks R package
   ([69]Colaprico et al., 2016). We then combined TCGA-COAD cohort and
   TCGA-READ cohort into TCGA-CRC cohort, which was used for our
   subsequent analysis. The TMB of TCGA-CRC was downloaded from the
   previous literature ([70]Lin et al., 2020). Clinical basic information
   about Local-CRC, Mondaca-CRC and TCGA-CRC are defined in
   [71]Supplementary Table S1–S3, respectively.

Definition of the Abrupt State of HR Pathway

   We downloaded the gene list of KEGG_HOMOLOGOUS_RECOMBINATION
   ([72]Supplementary Table S4) from MsigDB database ([73]Liberzon et al.,
   2011). Firstly, the synonymous mutations in the mutation data from
   Local-CRC, Mondaca-CRC and TCGA-CRC were deleted, retaining only the
   mutation data of non-synonymous mutation types. According to the gene
   list of KEGG_homologus_recombination (HR), we counted the mutation
   number of the HR pathway in each patient. When the number of gene
   mutations in a patient’s HR pathway was zero, we labeled it the HR
   wild-type (WT). Otherwise, they were referred to as the HR mutant-type
   (MUT).

Relationship Between HR Pathway Mutation and Prognosis or Curative Effect of
CRC Patients

   We used logistic regression analysis to explore the relationship
   between the mutation status of HR pathway and whether Local-CRC
   patients had metastasis after receiving chemotherapy. In Mondaca-CRC
   cohort, univariable and multivariate Cox regression analysis, as well
   as Kaplan-Meier analysis, were used to evaluate the influence of HR
   pathway mutation on the survival time of CRC patients after receiving
   chemotherapy.

Path Enrichment Analysis

   Using clusterProfiler R package and gene set enrichment analysis (GSEA)
   ([74]Yu et al., 2012), we analyzed the expression profile data of the
   HR-MUT and HR-WT groups and compared the enrichment scores and p values
   of the HR-MUT and HR-WT groups to those of GO-BP, GO-CC, GO-MF, KEGG,
   and REACTOME. We also used single sample GSEA (ssGSEA) to analyze the
   pathway score of each CRC patient ([75]Lin et al., 2022).

Statistical Analysis

   The Mann-Whitney U test was used to compare the differences between the
   continuity variables of the HR-MUT and HR-WT groups, while Fisher’
   exact test was used to compare the differences in the classification
   variables of the HR-MUT and HR-WT groups. The log-rank test in
   combination with Kaplan-Meier analysis was used to calculate the p
   value. All statistical analysis and visual analysis in this study were
   based on R language. Here, the p value was bilateral and any p value of
   less than 0.05 was regarded as statistically significant.

Results

HR-MUT is Related to a Better Curative Effect and Prognosis in CRC Patients
Receiving Chemotherapy

   In order to explore the relationship between the mutation state of HR
   pathway and the chemotherapy efficacy and prognosis of CRC patients
   ([76]Figure 1), we first analyzed whether HR-MUT can influence the
   presence of tumor metastasis in CRC patients after chemotherapy
   ([77]Figure 2A). The results showed that HR-MUT might indeed cause less
   tumor metastasis in CRC patients after chemotherapy (OR < 0; p < 0.05).
   The results displayed in [78]Figure 2B demonstrate how HR-WT was often
   found in CRC patients without tumor metastasis after chemotherapy (p <
   0.05). Meanwhile, as shown in [79]Figure 2C, CRC patients with HR-MUT
   often did not display any tumor metastasis after receiving chemotherapy
   (p < 0.05). For Mondaca-CRC patients, our univariable and multivariate
   Cox regression analysis showed that HR-MUT could be used as an
   independent predictor of chemotherapy prognosis for CRC patients
   ([80]Figure 2D). Notably, the Kaplan-Meier curve showed that HR-MUT had
   significantly longer OS time than HR-WT (log-rank p = 0.017; HR = 0.69;
   [81]Figure 2E).

FIGURE 1.

   [82]FIGURE 1
   [83]Open in a new tab

   Overall design of the study.

FIGURE 2.

   [84]FIGURE 2
   [85]Open in a new tab

   The prognosis value of the HR-MUT group (A). Logistic regression model
   of the HR-MUT group and clinical characteristics in the Local-CRC
   cohort (B). A comparison between the HR mutation statuses of the
   metastasis-yes group and metastasis-no group (C). A comparison between
   the tumor metastasis statuses of the HR-MUT and HR-WT groups (D). The
   univariable and multivariable cox regression model of the HR-MUT group
   and clinical characteristics in the Mondaca-CRC cohort (E). KM curve
   showed the HR-MUT CRC patients displayed a significant improvement in
   OS time compared with the HR-WT CRC patients in the Mondaca-CRC cohort
   (*p < 0.05).

   In order to further verify the relationship between HR-MUT and the
   sensitivity of chemotherapeutic drugs, we evaluated the IC50 value of
   several chemotherapeutic drugs using pRRophetic algorithm combined with
   the CRC patient expression data. From this analysis, we found that
   HR-MUT group displayed a significantly lower IC50 value with the
   chemotherapeutic drugs than the HR-WT group ([86]Figure 3).

FIGURE 3.

   [87]FIGURE 3
   [88]Open in a new tab

   A comparison between the IC50 values of common chemotherapy drugs used
   on HR-MUT and the HR-WT CRC patients (*p < 0.05; **p < 0.01; ***p <
   0.001; ****p < 0.0001).

HR-MUT is Associated With Higher Mutation Frequency, TMB, and MSIscore

   Next, we compare the gene mutation frequencies of the HR-MUT and HR-WT
   groups to the top 20 mutation frequencies found in the other CRC
   cohorts. For Local-CRC, the HR-MUT group had significantly higher
   mutation frequency than the HR-WT group in Gli3 (42.9% vs. 3.6%), BRCA2
   (42.9% vs. 0.0%), and ITGB2 (42.9% vs. 0.0%) (all p < 0.05; [89]Figure
   4A). In Mondaca-CRC, the HR-MUT group was notably higher than the HR-WT
   group in RNF43 (17.3% vs. 6.2%), ARID1A (21.0% vs. 4.9%), KMT2D (22.2%
   vs. 4.7%), PTPRS (18.5% vs. 4.7%), ERBB4 (12.3% vs. 4.1%), PTPRT (11.1%
   vs. 4.1%), NF1 (9.9% vs. 4.1%), and PTEN (11.1% vs. 3.6%), all of which
   had significantly increased mutation frequency (all p < 0.05;
   [90]Figure 4B). [91]Supplementary Figures S1A,B shows the mutual
   exclusion and co-occurrence of the top 20 gene mutations in the
   Local-CRC and Mondaca-CRC cohorts, respectively, while
   [92]Supplementary Figures S2A,B show the gene mutation of HR-MUT
   patients in the Local-CRC Cohort and Mondaca-CRC Cohort, respectively.

FIGURE 4.

   [93]FIGURE 4
   [94]Open in a new tab

   The mutation profiles of the HR-MUT and HR-WT CRC patients. The
   mutational landscape of the top mutated gene mutations in the Local-CRC
   cohort (A) and Mondaca-CRC cohort (B). A comparison of the TMB levels
   of the HR-MUT group and HR-WT group in the Local-CRC cohort (C) and
   Mondaca-CRC cohort (D). A comparison between the MSI scores (E) and MSI
   statuses (F) the HR-MUT and HR-WT groups in the Mondaca-CRC cohort (*p
   < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001).

   Compared with HR-WT, HR-MUT displayed a significantly higher level of
   TMB in Local-CRC and Mondaca-CRC (p = 2.55e-04, [95]Figure 4C; P =
   5e-05, [96]Figure 4D). We also found that HR-MUT had a higher MSI score
   than HR-WT (p = 2.66e-02; [97]Figure 4E). Similarly, HR-MUT had a
   higher prevelence of instable MSI status (p < 0.0001; [98]Figure 4F).

HR-MUT is Related to the Less Active DNA Repair Ability of CRC Patients and
Promoting Tumor Metastasis and Metabolism

   In order to further explore the difference between HR-MUT and HR-WT in
   pathway activity, we utilized GSEA and ssGSEA. Compared with HR-WT,
   HR-MUT displayed a significant increase in immune activity, which is
   manifested by an increase in antigen presenting ability, infiltration
   and recruitment of CD4^+ T cells, and production of INF-gamma (ES > 0,
   p < 0.05, [99]Figure 5A; [100]Supplementary Table S5). Additionally,
   HR-MUT had significantly reduced tumor metabolic activity, as well as
   fatty acid metabolic activity (ES < 0, p < 0.05; [101]Figure 5B;
   [102]Supplementary Table S5). Compared with HR-WT, HR-MUT also had
   significantly reduced WNT pathway activity (ES < 0, p < 0.05;
   [103]Figure 5C; [104]Supplementary Table S5).

FIGURE 5.

   FIGURE 5
   [105]Open in a new tab

   The GSEA results. A comparison of the enrichment scores of
   immune-related (A), tumor metabolism (B) and tumor metastasis/growth
   (C) found in the HR-MUT and HR-WT groups based on the GSEA algorithm.

   In order to further verify the channel activity, we used the ssGSEA
   algorithm and obtained similar results ([106]Figures 6A–D). From this,
   we found that HR-MUT had significantly higher immune response ability
   than HR-WT ([107]Figure 6A), while HR-MUT had significantly lower DNA
   repair ability, tumor metabolism ability, and tumor metastasis ability
   ([108]Figures 6B–D).

FIGURE 6.

   [109]FIGURE 6
   [110]Open in a new tab

   The ssGSEA results. A comparison between the ssGSEA scores in the
   category of immune-related (A), DNA-related (B), metabolism-related (C)
   and tumor metastasis/growth related (D) of the HR-MUT and HR-WT based
   on the ssGSEA algorithm (*p < 0.05; **p < 0.01; ***p < 0.001; ****p <
   0.0001).

Discussion

   In this study, we found that HR-MUT is related to the reduced
   occurrence of tumor metastasis in CRC patients who have received
   chemotherapy. Additionally, HR-MUT was related to a significantly
   longer OS time than HR-WT for CRC patients receiving chemotherapy. More
   importantly, univariate and multivariate cox regression models showed
   that HR-MUT acts as an independent prognostic marker for CRC patients
   receiving chemotherapy. From the data derived from the genome level
   analysis, we found that HR-MUT CRC patients had significantly increased
   TMB and MSI scores, as well as MSI-Instable status, in comparison to
   HR-WT CRC patients. Based on the pathway enrichment analysis, HR-MUT
   patients displayed a significant reduction in their DNA repair ability,
   tumor survival or metastasis related activity, and tumor metabolic
   activity. Conversely, HR-MUT patients displayed a much higher level of
   immune response activity. We also found that HR-MUT CRC patients had a
   longer survival time after receiving immunotherapy than HR-WT CRC
   patients. Therefore, we speculate that HR-MUT may be a valuable
   prognostic marker for CRC patients receiving chemotherapy.

   The stronger immune response in the tumor microenvironment may be one
   of the potential mechanisms behind the better prognosis found in HR-MUT
   patients receiving chemotherapy. In the HR-MUT group, the activity of
   the interferon gamma production pathway was significantly higher than
   that of the HR-WT group. In this vein, studies have shown that although
   chemotherapeutic drugs can directly clear divided endothelial cells by
   inhibiting enzymes involved in DNA replication or microtubule
   metabolism, most of the vascular injuries may be caused by
   chemotherapy-induced inflammation ([111]Kerbel and Kamen, 2004;
   [112]Lee and Wu, 2015). This is due to the fact that in the process of
   tumor rejection induced by cyclopamine, immune downregulation is
   activated to produce interferon-γ (IFN-γ), thus inhibiting angiogenesis
   ([113]Ibe et al., 2001). IFNγ-γ-mediated vascular inhibition is one of
   the important anti-tumor mechanisms of T cells ([114]Qin and
   Blankenstein, 2000; [115]Kammertoens et al., 2017), as it can reduce
   the expression of Dll4 signaling pathway in endothelial cells, destroy
   the connection between endothelial cells, and resist angiogenesis in
   tumor tissue ([116]Deng et al., 2014). However, in a study on early
   treatment of tumors that combined IFNγ with chemotherapy, it was found
   that IFNγ could in fact increase the mortality rate ([117]Alberts et
   al., 2008; [118]Zarogoulidis et al., 2013). As for the activity of IL-6
   production, the rates in HR-MUT were significantly lower than that in
   HR-WT. Further research on this topic has revealed that IL-6 activates
   the STAT3 signaling pathway of tumor cells and promotes the expression
   of VEGF, thereby inducing angiogenesis ([119]Wei et al., 2003). We also
   found that the activation of macrophages in the HR-MUT group was
   significantly lower than that in the HR-WT group. Earlier research on
   this shows that macrophages are one of the main cell types in the tumor
   microenvironment, and they can promote cell survival and chemotherapy
   resistance by releasing interleukin -17 ([120]Guo et al., 2017).
   Similarly, according to an earlier study by Ruffell. et al., it was
   found that M2 macrophage inhibited the production of IL-12 by dendritic
   cells through the over-secretion of IL-10, therefore blocking the
   immune response of CD8+T cells ([121]Ruffell et al., 2014).

   Tumor metabolic reprogramming may also be one of the important
   mechanisms involved in CRC chemotherapy resistance. In our study, we
   found that lipid metabolism was significantly down-regulated in HR-MUT.
   Beyond our own results, other studies have confirmed that lipid
   metabolism rearrangement is involved in the regulation of the CRC cell
   chemotherapy resistance mechanism ([122]Fiucci et al., 2000; [123]Cotte
   et al., 2018), plays a role in the occurrence and development of CRC
   ([124]Hwang et al., 2014; [125]Liu et al., 2016; [126]Mihajlovic et
   al., 2019; [127]Liu et al., 2020), and has an impact on the prognosis
   ([128]de Figueiredo Junior et al., 2018). Research has also found that
   lipid droplets (LD) levels in CRC cells are significantly higher than
   in those of normal cells, indicating that it may play a key role in the
   development of CRC ([129]Accioly et al., 2008). Many studies have
   confirmed that lipid metabolism-related enzymes participate in the
   occurrence and development of CRC ([130]Liu et al., 2020), regulate
   cell proliferation and invasion ([131]Sánchez-Martínez et al., 2015;
   [132]Nath and Chan, 2016), and participate in drug resistance
   ([133]Fiucci et al., 2000; [134]Cotte et al., 2018). Because of this,
   fatty acids, phospholipids, and cholesterol are synthesized actively,
   and their concentrations are significantly increased in tumor tissues
   ([135]Janardhan et al., 2006; [136]Lupu and Menendez, 2006). With this
   in mind, some anti-tumor drugs have been developed to significantly
   reduce cell cholesterol levels by blocking different steps of
   cholesterol biosynthesis ([137]Eliassen et al., 2005; [138]Gorin et
   al., 2012; [139]Luu et al., 2013). Except for lipid metabolism, we
   found that the activity of glutathione synthesis in HR-MUT group was
   significantly lower than that in HR-WT group. Glutamine metabolism can
   also promote drug resistance in tumors by influencing the
   post-translational modification of proteins. Treatment with glutamine
   analogue DON can increase the sensitivity of pancreatic cancer to
   gemcitabine. In past studies, researchers have found that DON can
   inhibit hexosamine pathways, which leads to a change in the
   glycosylation level of protein groups in the cell as while. This
   ultimately affects the sensitivity of tumors to chemotherapy ([140]Chen
   et al., 2017). Additionally, glutamine metabolism can affect the drug
   resistance of tumors epigenetically. In KRAS mutant colon cancer cells,
   SLC25A22 promotes the accumulation of succinic acid, a metabolite of
   glutamine in the tricarboxylic acid cycle, which further increases the
   local methylation degree of DNA and then promotes the activation of Wnt
   signaling pathway. This sequence of events leads to tolerance of colon
   cancer cells to chemotherapeutic drugs ([141]Wong et al., 2020).

   In addition to immune response and tumor metabolism reprogramming,
   pathways related to tumor growth and metastasis may also be involved in
   CRC chemotherapy resistance. Based on GSEA and ssGSEA, we found that
   the WNT pathway activity was significantly upregulated in HR-WT.
   According to Nagaraj et al., the expression levels of β-catenin and
   survivin in A549 sensitive and drug-resistant cells were higher than
   those in sensitive cells after cisplatin treatment ([142]Nagaraj et
   al., 2015). Furthermore, Novetsky et al.‘s research indicated that
   inhibiting the activity of GSK-3β in cells can activate the WNT
   pathway, which mediates chemotherapy resistance ([143]Novetsky et al.,
   2013). Zhang et al. found that interfering with β-catenin using siRNA
   can improve the sensitivity of tumor cells to chemotherapeutic drugs,
   further proving that the WNT pathway plays an important role in
   chemotherapeutic drug resistance ([144]Zhang et al., 2015). In our own
   research, we found that VEGFR2 pathway was significantly activated in
   HR-WT. Similarly, Mann et al. inhibited the phosphorylation of VEGFR2
   in tumor cells and observed that while blood vessels in the tumor
   remained normal, the sensitivity of the tumor cells to chemotherapeutic
   drugs such as cyclophosphamide and cisplatin was enhanced
   ([145]Stockmann et al., 2008).

Conclusion

   In summary, our research shows that HR-MUT is associated with less
   tumor metastasis in CRC patients after receiving chemotherapy. The
   HR-MUT CRC patients had significantly improved OS time and, as such,
   HR-MUT could be used as a predictor of chemotherapy prognosis in the
   future treatment plan. Additionally, HR-MUT patients had higher TMB
   levels, MSI scores, and immune response activity, while they also had
   lower tumor survival, metastasis pathway activity, and tumor metabolic
   reprogramming activity. The activity of these pathways may greatly
   increase the sensitivity of HR-MUT patients to chemotherapy drugs.
   Therefore, HR-MUT may be used as a new predictive marker for CRC
   patients who are receiving chemotherapy treatment.

Data Availability Statement

   The original contributions presented in the study are included in the
   article/[146]Supplementary Material, further inquiries can be directed
   to the corresponding authors.

Ethics Statement

   The studies involving human participants were reviewed and approved by
   Guangxi Medical University Cancer Hospital. The patients/participants
   provided their written informed consent to participate in this study.

Author Contributions

   Conceptualization, YL and RL; Formal analysis, YL and XL;
   Visualization, YL and XL; Writing–original draft, YZ, GW, JY, SL, XH,
   ML, MX, JZ, QL, YH, SL, YL, and RL; Writing–review and editing, YL, XL,
   YZ, GW, JY, SL, XH, ML, MX, JZ, QL, YH, SL, YL, and RL. All authors
   read and approved the final manuscript.

Conflict of Interest

   The authors declare that the research was conducted in the absence of
   any commercial or financial relationships that could be construed as a
   potential conflict of interest.

Publisher’s Note

   All claims expressed in this article are solely those of the authors
   and do not necessarily represent those of their affiliated
   organizations, or those of the publisher, the editors and the
   reviewers. Any product that may be evaluated in this article, or claim
   that may be made by its manufacturer, is not guaranteed or endorsed by
   the publisher.

Supplementary Material

   The Supplementary Material for this article can be found online at:
   [147]https://www.frontiersin.org/articles/10.3389/fphar.2022.920939/ful
   l#supplementary-material
   Supplementary Figure S1

   The co-occurrence and mutually exclusive occurrence of the top 20
   mutated genes in the Local-CRC (A) and the Mondaca-CRC (B) cohorts.
   Supplementary Figure S2

   The mutation landscape of the HR mutations of the HR-MUT CRC patients
   in the Local-CRC (A) and the Mondaca-CRC (B) cohorts.
   Supplementary Table S1

   The clinical characteristics of the Local-CRC cohort.
   Supplementary Table S2

   The clinical characteristics of the Mondaca-CRC cohort.
   Supplementary Table S3

   The clinical characteristics of the TCGA-CRC cohort.
   Supplementary Table S4

   The gene set of the HR signaling used in this study.
   Supplementary Table S5

   The GSEA result of the enrichment scores between the HR-MUT and HR-WT
   groups based on the GSEA algorithm.
   [148]Click here for additional data file.^ (459.4KB, PDF)
   [149]Click here for additional data file.^ (8.9KB, XLSX)
   [150]Click here for additional data file.^ (273.9KB, PDF)
   [151]Click here for additional data file.^ (243.1KB, PDF)
   [152]Click here for additional data file.^ (310.5KB, PDF)
   [153]Click here for additional data file.^ (10KB, XLSX)
   [154]Click here for additional data file.^ (282.5KB, PDF)

Abbreviation

   CRC, colorectal cancer; ECOG, Eastern Cooperative Oncology Group
   Performance Status; GSEA, gene set enrichment analysis; HR, Homologous
   recombination; HR-MUT, HR mutant-type; HR-WT, HR wild-type; IC50, half
   maximal inhibitory concentration; HRD, homologous recombination defect;
   LD, lipid droplets; IFN-γ, interferon-γ; MSI: Microsatellite
   instability; NER, Nucleotide excision repair; OS, overall survival;
   TMB, Tumor mutational burden, ssGSEA, single sample gene set enrichment
   analysis.

References