Mutant-allele Tumor Heterogeneity Research Articles

Impact of intratumor heterogeneity (ITH) on survival outcomes in patients with non-small cell lung cancer (NSCLC) with high tumor mutational burden (TMB-H).

e20519 Background: Heterogeneity among cancer cells within a tumor significantly impacts cancer development and resistance to treatment. Currently, no standard measure exists for assessing ITH in routine clinical settings. In this study, we applied a quantitative metric to assess intratumor genetic diversity in NSCLC, using a large, multicenter database. Methods: We accessed the Tempus database for next-generation sequencing results from patients with NSCLC who underwent immune checkpoint inhibitor (ICIs) monotherapy as their first-line treatment. We calculated the mutant-allele tumor heterogeneity (MATH), defined as the ratio of the distribution's range to the median of mutant-allele fractions across tumor-specific mutated loci. The primary outcomes were progression-free survival (PFS) and overall survival (OS). Results: A total of 160 pembrolizumab Significant differences in PFS between high and low MATH groups (MATH-H and MATH-L, respectively), using the 50th percentile as the cutoff, were observed among patients with stage 4 adenocarcinoma who had TMB-H above the 25th percentile (Table). In this subgroup, with 27 patients in the MATH-H/TMB-H group and 22 in the MATH-L/TMB-H group, the MATH-H/TMB-H group showed improved PFS (median PFS 5.19 vs. 1.61 months; p = 0.02). Differences in PFS were also observed among patients with TP53, KEAP1, and MET mutations (p < 0.001, p = 0.02, and p = 0.004, respectively). TP53 mutations were found in 27.6% of the MATH-H group and 27.8% of the MATH-L group, KEAP1 mutations in 8.2% and 10.1%, respectively, and MET mutations in 5.1% and 8.9%, respectively. No significant PFS differences were found in groups with low TMB, other stages, or squamous histology. Conclusions: Our findings suggest that higher genetic diversity within stage 4 TMB-H lung adenocarcinoma, as quantified by MATH, might be linked to improved clinical outcomes among those who receive pembrolizumab as first-line therapy and supports further exploration of MATH as a predictive/prognostic biomarker. [Table: see text]

Comprehensive molecular characterization of long-term glioblastoma survivors

Fewer than 5 % glioblastoma (GBM) patients survive over five years and are termed long-term survivors (LTS), yet their molecular background is unclear. The present cohort included 72 isocitrate dehydrogenase (IDH)-wildtype GBM patients, consisting of 35 LTS and 37 short-term survivors (STS), and we employed whole exome sequencing, RNA-seq and DNA methylation array to delineate this largest LTS cohort to date. Although LTS and STS demonstrated analogous clinical characters and classical GBM biomarkers, CASC5 (P = 0.002) and SPEN (P = 0.013) mutations were enriched in LTS, whereas gene-to-gene fusions were concentrated in STS (P = 0.007). Importantly, LTS exhibited higher tumor mutation burden (P < 0.001) and copy number (CN) increase (P = 0.013), but lower mutant-allele tumor heterogeneity score (P < 0.001) and CN decrease (P = 0.026). Additionally, LTS demonstrated hypermethylated genome (P < 0.001) relative to STS. Differentially expressed and methylated genes both enriched in olfactory transduction. Further, analysis of the tumor microenvironment revealed higher infiltration of M1 macrophages (P = 0.043), B cells (P = 0.016), class-switched memory B cells (P = 0.002), central memory CD4+ T cells (P = 0.031) and CD4+ Th1 cells (P = 0.005) in LTS. We also separately analyzed a subset of patients who were methylation class-defined GBM, contributing 70.8 % of the entire cohort, and obtained similar results relative to prior analyses. Finally, we demonstrated that LTS and STS could be distinguished using a subset of molecular features. Taken together, the present study delineated unique molecular attributes of LTS GBM.

Abstract PO1-07-11: Radiogenomic-based imaging intratumor heterogeneity model predicts breast cancer prognosis and unveils therapeutic targets

Abstract Background: Intratumor heterogeneity (ITH) refers to variations observed among cancer cells within a single tumor, posing significant challenges in clinical practice due to its contribution to treatment resistance and unfavorable outcome. However, the inconvenience of multi-region biopsy and limitations of genomic sequencing based on limited tissue impede the practical detection of ITH. Consequently, there is an urgent need for a non-invasive method that comprehensively captures ITH from a holistic perspective of the entire tumor. Methods: We utilized a large multicenter dataset comprising dynamic contrast-enhanced magnetic resonance images from breast cancer patients (n = 1423) along with matched multiomics data (n = 468) to develop a non-invasive machine learning approach for measuring ITH. We extracted quantitative radiomic features from both the entire tumor and peritumor regions, with a specific focus on features associated with imaging heterogeneity. Using these radiomic features, we established an imaging ITH (IITH) model. The robustness of IITH evaluation was determined by assessing its correlation with genomic ITH (employing the mutant-allele tumor heterogeneity [MATH] algorithm) and pathological cellular ITH (analyzing variation in quantitative nuclear features extracted through digital pathology). Prognostic power was evaluated using Kaplan-Meier and multivariate Cox proportional hazards analyses. Integrated multiomics analyses were performed to investigate the molecular basis of different IITH subgroups. Results: We developed a non-invasive radiomic signature to quantify imaging ITH (IITH) in the FUSCC cohort. Breast cancer patients were retrospectively categorized into high and low IITH groups. Multivariate Cox analysis identified high IITH as an independent predictor of poor prognosis in breast cancer patients, even after adjusting for clinical risk factors such as tumor size, positive lymph nodes, clinical subtype and lymphovascular invasion status. These findings were further validated in the DUKE cohort, confirming the prognostic value of IITH. Moreover, we substantiated the robustness of IITH by demonstrating its association with genomic and pathological ITH. Multiomics analysis revealed the activation of oncogenic pathways and metabolic dysregulation in high-IITH tumors. Intriguingly, our investigation also highlighted ferroptosis as a vulnerability and potential therapeutic target in high-IITH tumors, which was further supported by evidence from the TCGA cohort. Conclusion: Radiomic-based assessment of ITH provides a non-invasive approach to comprehensively capture ITH and predict the prognosis of breast cancer patients. Targeting ferroptosis may hold promise as a treatment strategy for patients with high IITH. Citation Format: Guan-Hua Su, Yi Xiao, Chao You, Ren-Cheng Zheng, Shen Zhao, He Wang, Yi-Zhou Jiang, Ya-Jia Gu, Zhi-Ming Shao. Radiogenomic-based imaging intratumor heterogeneity model predicts breast cancer prognosis and unveils therapeutic targets [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-11.

Pan-cancer analysis reveals correlation between RAB3B expression and tumor heterogeneity, immune microenvironment, and prognosis in multiple cancers

RAB3B is essential for the transportation and secretion within cells. Its increased expression is linked to the development and progression of various malignancies. However, understanding of RAB3B’s involvement in carcinogenesis is mostly limited to specific cancer subtypes. Hence, exploring RAB3B's regulatory roles and molecular mechanisms through comprehensive cancer datasets might offer innovative approaches for managing clinical cancer. To examine the potential involvement of RAB3B in the development of cancer, we analyzed data from various sources including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), cBioPortal, HPA, UALCAN, and tissue microarray (TAM). Using bioinformatics techniques, we examined the correlation between RAB3B expression and prognosis, tumor heterogeneity, methylation modifications, and immune microenvironment across different cancer types. Our findings indicate that elevated RAB3B expression can independently predict prognosis in many tumors and has moderate accuracy for diagnosing most cancers. In most cancer types, we identified RAB3B mutations that showed a significant correlation with tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), and microsatellite instability (MSI). Abnormal DNA methylation patterns were also observed in most cancers compared to normal tissues. Additionally, we found significant correlations between RAB3B expression, immune cell infiltration, and immune scores across various cancers. Through pan-cancer analysis, we observed significant differences in RAB3B expression levels between tumors and normal tissues, making it a potential primary factor for cancer diagnosis and prognosis. The IHC results revealed that the expression of RAB3B in six types of tumors was consistent with the results of the pan-cancer analysis of the database. Furthermore, RAB3B showed potential associations with tumor heterogeneity and immunity. Thus, RAB3B can be utilized as an auxiliary diagnostic marker for early tumor detection and a prognostic biomarker for various tumor types.

Identification of molecular subtypes based on chromatin regulator-related genes and experimental verification of the role of ASCL1 in conferring chemotherapy resistance to breast cancer.

The aim of this study was to identify the molecular subtypes of breast cancer based on chromatin regulator-related genes. The RNA sequencing data of The Cancer Genome Atlas-Breast Cancer cohort were obtained from the official website, while the single-cell data were downloaded from the Gene Expression Omnibus database (GSE176078). Validation was performed using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Furthermore, the immune characteristics, tumor stemness, heterogeneity, and clinical characteristics of these molecular subtypes were analyzed. The correlation between chromatin regulators and chemotherapy resistance was examined in vitro using the quantitative real-time polymerase chain reaction (qRT-PCR) and Cell Counting Kit-8 (CCK8) assays. This study identified three stable molecular subtypes with different prognostic and pathological features. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses revealed that the differentially expressed genes were associated with disease processes, such as mitotic nuclear division, chromosome segregation, condensed chromosome, and specific chromosome region. The T stage and subtypes were correlated with the clinical features. Tumor heterogeneity (mutant-allele tumor heterogeneity, tumor mutational burden, purity, and homologous recombination deficiency) and tumor stemness (RNA expression-based stemness score, epigenetically regulated RNA expression-based stemness score, DNA methylation-based stemness score, and epigenetically regulated DNA methylation-based stemness score) significantly varied between the three subtypes. Furthermore, Western blotting, qRT-PCR, and CCK8 assays demonstrated that the expression of ASCL1 was positively correlated with chemotherapy resistance in breast cancer. This study identified the subtypes of breast cancer based on chromatin regulators and analyzed their clinical features, gene mutation status, immunophenotype, and drug sensitivity. The results of this study provide effective strategies for assessing clinical prognosis and developing personalized treatment strategies.

Coactosin-Like Protein 1 (COTL1) Could Be an Immunological and Prognostic Biomarker: From Pan-Cancer Analysis to Low-Grade Glioma Validation.

Cancer represents a widespread global health challenge impacting millions of individuals worldwide. Identifying new targets for cancer treatment is a crucial step in developing more effective therapies. Among these potential targets, Coactosin-like protein 1 (COTL1), a cytoskeleton-associated protein with critical roles in cell migration, adhesion, and signaling, has shown involvement in tumor progression. GSCA, TIMER, SangerBox database were used to explore the COTL1 expression across different tumor types. We employed the TCGA Pan-Atlas Cancer Genomics Dataset, which is available through the cBioportal platform, to explore genetic alterations in COTL1. We conduct a comprehensive analysis of COTL1, encompassing gene expression, clinical prognosis, RNA modification, immunotherapy, and cancer stemness through SangerBox database. Clinical samples were validated using immunohistochemistry. Our analysis revealed that COTL1 is highly expressed in most cancers and correlates with decreased survival in Glioma, Glioblastoma multiforme, and pan-kidney cohorts. Furthermore, COTL1 was found to be associated with DNA and RNA stemness in 20 and 22 different tumor types, respectively. Additionally, COTL1 showed positive correlations with immunological checkpoints and immune infiltration cells. It was also linked to tumor mutation burden (TMB), microsatellite instability (MSI), neoantigen (NEO), and programmed death ligand 1 (PD-L1), all of which are potential targets for immunotherapies. Moreover, a favorable relationship was demonstrated between genomic-instability markers such as heterozygosity (LOH), homologous recombination deficiency (HRD), and mutant allele tumor heterogeneity (MATH) with COTL1. Furthermore, our findings confirmed a positive correlation between COTL1 expression, CD8, and PD-L1 in LGG, as well as an association of high COTL1 expression with decreased patient survival in LGG. Based on these compelling findings, COTL1 may hold significant clinical implications for the development of novel cancer therapies and serve as a potential target for tumors associated with immunotherapy in the future.

CCDC71L as a novel prognostic marker and immunotherapy target via lipid metabolism in head and neck squamous cell carcinoma

BackgroundHead and neck squamous cell carcinoma (HNSCC) is the sixth most widespread cancer globally with high rate and poor prognosis. Coiled-coil domain containing 71 like (CCDC71L) exerts an important role in cellular lipid metabolic process. However, its function in HNSCC remains unclear. To this end, we examined the CCDC71L implications for prognosis and tumor microenvironment in HNSCC. Materials and methodsFirst, CCDC71L expression was explored through The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), the Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Gene Expression Omnibus (GEO) databases. The clinicpathological information were obtained from the dataset of TCGA. The Kaplan–Meier Plotter databases and Cox model were performed for the determination of prognostic values of CCDC71L, including the overall survival (OS), progress free interval (PFI), recurrence-free survival (RFS) and disease specific survival (DSS). Then, the potential mechanism of CCDC71L in HNSCC development was elucidated by means of Gene set enrichment analysis (GSEA) and Metascape databases. Furthermore, the relevance of CCDC71L to immune cells infiltration and immune checkpoints was assessed. The correlations among CCDC71L expression, mutational landscape and genome heterogeneity [mutant-allele tumor heterogeneity (MATH) and tumor purity] were detected by the data in TCGA. ResultsCCDC71L expression was significantly upregulated in HNSCC, and positively associated with age, gender and N stage. Higher CCDC71L expression resulted in poor OS, RFS, DSS and PFI. Multivariate Cox regression analysis showed CCDC71L would be an independent prognostic marker in patients with HNSCC. Moreover, CCDC71L and the level of macrophage and neutrophil cells infiltration were significantly correlated in HNSCC. High expression of CCDC71L was related to immune checkpoint genes, oncogene mutations and genome heterogeneity markers. ConclusionThese results implied that CCDC71L plays vital roles in HNSCC progression, which could be used as a underlying biomarker for the diagnosis and prognosis of HNSCC. Meanwhile, CCDC71L participates in immune regulation, which has a potential value for the immunotherapy of HNSCC patients.

The loss of neoantigens is an important reason for immune escape in multiple myeloma patients with high intratumor heterogeneity.

Intratumor heterogeneity (ITH) is an important factor for clinical outcomes in patients with multiple myeloma (MM). High ITH has been proven to be a key reason for tumor immune escape and treatment resistance. Neoantigens are thought to be associated with ITH, but the specific correlation and functional basis for this remains unclear. We study this question through the whole-exome sequencing (WES) data from 43 high ITH newly diagnosed MM patients in our center. Mutant allele tumor heterogeneity (MATH) was conducted to quantify ITH. The cutoff value for high intratumor heterogeneity was determined by comparing MATH of different kinds of tumors. NeoPredPipe was performed to predict neoantigens and binding affinity. Compared to other tumors, MM has a relatively low tumor mutation burden but a high ITH. Patients with high MATH had significantly shorter progression-free survival times than those with low MATH (p = 0.001). In high ITH samples, there is a decrease in strong-binding neoantigens (p = 0.019). The loss of strong-binding neoantigens is a key factor for insensitivity to therapy (p = 0.015). Loss of heterozygosity in HLA was not observed. In addition, patients with fewer neoantigens loss had higher rates of disease remission (p = 0.047). CD8 + T cells (p = 0.012) and NK cells (p = 0.011) decreased significantly in patients with high neoantigens loss rate. A prediction model based on neoantigens was built to evaluate the strength of immune escape. The loss of strong-binding neoantigens explains why tumors with high ITH have a higher degree of immune escape and may be feasible for deciding the clinical treatment of MM.

Dynamic analysis of circulating tumor DNA to predict the prognosis and monitor the treatment response of patients with metastatic triple-negative breast cancer: A prospective study

Background:Limited data are available on applying circulating tumor DNA (ctDNA) in metastatic triple-negative breast cancer (mTNBC) patients. Here, we investigated the value of ctDNA for predicting the prognosis and monitoring the treatment response in mTNBC patients.Methods:We prospectively enrolled 70 Chinese patients with mTNBC who had progressed after ≤2 lines of chemotherapy and collected blood samples to extract ctDNA for 457-gene targeted panel sequencing.Results:Patients with ctDNA+, defined by 12 prognosis-relevant mutated genes, had a shorter progression-free survival (PFS) than ctDNA− patients (5.16 months vs. 9.05 months, p=0.001), and ctDNA+ was independently associated with a shorter PFS (HR, 95% CI: 2.67, 1.2–5.96; p=0.016) by multivariable analyses. Patients with a higher mutant-allele tumor heterogeneity (MATH) score (≥6.316) or a higher ctDNA fraction (ctDNA%≥0.05) had a significantly shorter PFS than patients with a lower MATH score (5.67 months vs.11.27 months, p=0.007) and patients with a lower ctDNA% (5.45 months vs. 12.17 months, p&lt;0.001), respectively. Positive correlations with treatment response were observed for MATH score (R=0.24, p=0.014) and ctDNA% (R=0.3, p=0.002), but not the CEA, CA125, or CA153. Moreover, patients who remained ctDNA+ during dynamic monitoring tended to have a shorter PFS than those who did not (3.90 months vs. 6.10 months, p=0.135).Conclusions:ctDNA profiling provides insight into the mutational landscape of mTNBC and may reliably predict the prognosis and treatment response of mTNBC patients.Funding:This work was supported by the National Natural Science Foundation of China (Grant No. 81902713), Natural Science Foundation of Shandong Province (Grant No. ZR2019LZL018), Breast Disease Research Fund of Shandong Provincial Medical Association (Grant No. YXH2020ZX066), the Start-up Fund of Shandong Cancer Hospital (Grant No. 2020-PYB10), Beijing Science and Technology Innovation Fund (Grant No. KC2021-ZZ-0010-1).

Genomic profiling and immune landscape of olfactory neuroblastoma in China.

Olfactory neuroblastoma (ONB) is a rare malignant neoplasm of the olfactory mucosa. The paucity of genomic data has prevented the development of individualized ONB treatments. Here, we investigated the genomic and immune landscape of ONB in Chinese patients. Whole exome sequencing (WES) and multiplex immunofluorescence (MIF) analysis were performed on tissue samples from 19 Chinese ONB patients. Patients were divided into low- and high-grade groups. Overall, 929 nonsynonymous alterations were identified in 18 (94.74%) ONB cases. The most prevalent altered cancer-related genes were CTNNB1 (16%) and ZNRF3 (16%). The most mutated oncogenic pathways were the WNT and RAS pathways. The median tumor mutation burden (TMB) was 0.45, ranging from 0 to 3.25. Only one case expressed PD-L1 (> 1%) in the tumor region. The percentage of CD8+ tumor-infiltrating lymphocytes (TILs) in the tumor region ranged from 0.03% to 84.9%, with a median of 1.08%. No significant differences were observed between the low- and high-grade groups for clinicopathological features, mutant genes, mutant pathways, TMB, tumor neoantigen burden (TNB), mutant-allele tumor heterogeneity (MATH), PD-L1 expression levels, or CD8+ TIL percentage. However, the low-grade group showed significantly more CD68+ macrophages in both the tumor and total region than the high-grade group. Notably, CD68+CD163- macrophages accounted for an average of 80.5% of CD68+ macrophages. This study presents data on the genomic and immune landscape of ONB cases in China. CTNNB1 and ZNRF3 were the most prevalent altered cancer-related genes. The results of TMB, PD-L1, and CD8+ Tils suggest that ONB may be insensitive to immunotherapy. M1 macrophages may be positively associated with the prognosis of ONB. In this study, the most prevalent altered cancer-related genes were CTNNB1 (16%) and ZNRF3 (16%). The most mutated oncogenic pathways were the WNT and RAS pathways. The median tumor mutation burden (TMB) was 0.45, ranging from 0 to 3.25. Only one (1/15) case expressed PD-L1 (> 1%) in the tumor region. However, the low-grade group showed significantly more CD68+ macrophages in both the tumor and total region than the high-grade group. The higher level of CD68-related macrophages indicates that M1 macrophages potentially play an important role in ONB development that is possibly associated with prognosis.

Transmembrane serine protease 2, a SARS-CoV-2 internalization protease, correlates with clinical outcome, molecular features, and immunotherapy response in colorectal cancer.

Transmembrane serine protease 2 (TMPRSS2) mediates the entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) into host cells. The relevant research indicates the intestine to be a target of SARS-CoV-2 infection, and thus we aimed to investigate the correlation between TMPRSS2 expression and the prognosis, molecular features, and immunotherapy response in patients with colorectal cancer (CRC). The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used in this study and a total of 1,385 patients were identified. The CIBERSORT algorithms were used to evaluate the relative infiltration levels of immune cell types in the tumor microenvironment (TME). The correlation between TMPRSS2 expression and immunotherapy response rate was assessed in another 2 independent cohorts. TMPRSS2 expression was significantly downregulated in cancer tissue compared to the adjacent normal tissue, and patients with CRC with lower TMPRSS2 expression showed notably poorer prognosis. Functional enrichment analysis found that low TMPRSS2 expression was significantly associated with cancer metastasis-related pathways. Further analysis based on the miRWalk tool and JASPAR database identified a list of microRNAs (miRNAs) and transcriptional factors targeting TMPRSS2. Distinct differences in immune cell infiltration and tumor purity reflected by estimate and mutant-allele tumor heterogeneity score were observed between patients with low and high TMPRSS2 expression levels. Interestingly, patients with a low TMPRSS2 expression level showed a higher response rate to immunotherapy. CRC cells may be more resistant to SARS-CoV-2 infection due to the decreased expression of TMPRSS2, which could be a newly identified biomarker for prognosis and immunotherapy response prediction in patients with CRC.

The heterogeneity and clonal evolution analysis of the advanced prostate cancer with castration resistance

BackgroundNowadays, the incidence rate of advanced and metastatic prostate cancer at the first time of diagnosis grows higher in China yearly. At present, androgen deprivation therapy (ADT) is the primary treatment of advanced prostate cancer. However, after several years of ADT, most patients will ultimately progress to castration-resistant prostate cancer (CRPC). Previous studies mainly focus on Caucasian and very few on East Asian patients.MethodsIn this study, the pre- and post-ADT tumor samples were collected from five Chinese patients with advanced prostate cancer. The whole-exome sequencing, tumor heterogeneity, and clonal evolution pattern were analyzed.ResultsThe results showed that the gene mutation pattern and heterogeneity changed significantly after androgen deprivation therapy. Tumor Mutational Burden (TMB) and Copy Number Alteration (CNA) were substantially reduced in the post-treatment group, but the Mutant-allele tumor heterogeneity (MATH), Socio-Demographic Index (SDI), Intratumor heterogeneity (ITH), and weighted Genome Instability Index (wGII) had no significant difference. According to the clone types and characteristics, the presence of main clones in five pre-and post-treatment samples, the clonal evolution pattern can be further classified into two sub-groups (the Homogeneous origin clonal model or the Heterogeneous origin clonal model). The Progression-free survival (PFS) of the patients with the “Homogeneous origin clonal model” was shorter than the “Heterogeneous origin clonal model”. The longer PFS might relate to MUC7 and MUC5B mutations repaired. ZNF91 mutation might be responsible for resistance to ADT resistance.ConclusionOur findings revealed potential genetic regulators to predict the castration resistance and provide insights into the castration resistance processes in advanced prostate cancer. The crosstalk between clonal evolution patterns and tumor microenvironment may also play a role in castration resistance. A multicenter-research including larger populations with different background are needed to confirm our conclusion in the future.

The signature of cuproptosis-related immune genes predicts the tumor microenvironment and prognosis of prostate adenocarcinoma.

Cuproptosis plays a crucial role in cancer, and different subtypes of cuproptosis have different immune profiles in prostate adenocarcinoma (PRAD). This study aimed to investigate immune genes associated with cuproptosis and develop a risk model to predict prognostic characteristics and chemotherapy/immunotherapy responses of patients with PRAD. The CIBERSORT algorithm was used to evaluate the immune and stromal scores of patients with PRAD in The Cancer Genome Atlas (TCGA) cohort. Validation of differentially expressed genes DLAT and DLD in benign and malignant tissues by immunohistochemistry, and the immune-related genes of DLAT and DLD were further screened. Univariable Cox regression were performed to select key genes. Least absolute shrinkage and selection operator (LASSO)-Cox regression analyse was used to develop a risk model based on the selected genes. The model was validated in the TCGA, Memorial Sloan-Kettering Cancer Center (MSKCC) and Gene Expression Omnibus (GEO) datasets, as well as in this study unit cohort. The genes were examined via functional enrichment analysis, and the tumor immune features, tumor mutation features and copy number variations (CNVs) of patients with different risk scores were analysed. The response of patients to multiple chemotherapeutic/targeted drugs was assessed using the pRRophetic algorithm, and immunotherapy was inferred by the Tumor Immune Dysfunction and Exclusion (TIDE) and immunophenoscore (IPS). Cuproptosis-related immune risk scores (CRIRSs) were developed based on PRLR, DES and LECT2. High CRIRSs indicated poor overall survival (OS), disease-free survival (DFS) in the TCGA-PRAD, MSKCC and GEO datasets and higher T stage and Gleason scores in TCGA-PRAD. Similarly, in the sample collected by the study unit, patients with high CRIRS had higher T-stage and Gleason scores. Additionally, higher CRIRSs were negatively correlated with the abundance of activated B cells, activated CD8+ T cells and other stromal or immune cells. The expression of some immune checkpoints was negatively correlated with CRIRSs. Tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH) and copy number variation (CNV) scores were all higher in the high-CRIRS group. Multiple chemotherapeutic/targeted drugs and immunotherapy had better responsiveness in the low-CRIRS group. Overall, lower CRIRS indicated better response to treatment strategies and better prognostic outcomes.

Prognostic and immunomodulatory roles of schizophrenia-associated genes HTR2A, COMT, and PRODH in pan-cancer analysis and glioma survival prediction model.

The shortened life expectancy in schizophrenia (SCZ) patients may be correlated with most cancers, yet there is heterogeneity in the studies examining these correlations. This study explored the expression of SCZ-related genes (HTR2A, COMT, and PRODH) in pan-cancer analysis. It helped to enhance the mechanistic understanding of the SCZ-cancer relationship and their immune mechanisms at the genetic level. Additionally, this study established a survival prediction model for glioblastoma and low-grade glioma (GBMLGG). SCZ-associated genes (HTR2A, COMT, and PRODH) were subjected to pan-cancer analysis. COX regression analysis and survival analysis were carried out for differentially expressed genes in multiple cancers, and finally, GBMLGG was derived as the focus for further detailed analysis. The immune scores and immune cell infiltration analyses were performed. All three genes were considerably linked with immune infiltration in GBMLGG, consistent with survival analysis. Based on the immunocyte analysis, it was observed that CD8+ T cells might be critically involved in the survival of GBMLGG. Genomic heterogeneity studies identified correlations of three genes with GBMLGG in tumor mutational burden (TMB) and mutant-allele tumor heterogeneity (MATH). HTR2A and COMT were significantly negatively correlated in TMB. Furthermore, it was found that HTR2A had a significant positive correlation with MATH, whereas PRODH had a significant negative correlation with MATH. Accordingly, a survival prediction model was constructed for GBMLGG using these three genes and clinical data, with better results obtained when evaluated in two separate datasets. Finally, gene expression validation and further immunocyte analysis were carried out in the single-cell RNA sequencing (scRNA-seq) data of glioma. SCZ-associated genes (HTR2A, COMT, and PRODH) were significantly differentially expressed in the carcinogenesis and survival of multiple cancers. The up or downregulation of gene expression varied across cancer types. In the GBMLGG analysis, upregulation of HTR2A and COMT was significantly positively correlated with carcinogenesis, while the opposite was noted for PRODH. Furthermore, a negative correlation was found between the upregulation of HTR2A and COMT and the survival of GBMLGG, and the opposite was also noted for PRODH. As reflected in the immunocyte analysis, abnormal expression of the three genes might be linked with CD8+ T cell infiltration, which might be critically involved in the survival of GBMLGG patients. The expression of HTR2A and COMT may inversely affect the efficacy of immunotherapy through the TMB pathway and further affect the prognosis of patient survival. The expression of HTR2A might positively indicate the degree of tumor heterogeneity through MATH and further affect the survival and prognosis of patients. The negative correlation of PRODH led to the opposite effect. Finally, the constructed survival prediction model demonstrated good predictive value, which was well validated in scRNA-seq analysis.

Chronic obstructive pulmonary disease alters the genetic landscape and tumor immune microenvironment in lung cancer patients.

Chronic obstructive pulmonary disease (COPD) and lung cancer are leading causes of morbidity and mortality worldwide. Studies have reported molecular alterations in patients with lung cancer and in patients with COPD. However, few investigation has been conducted on the molecular characteristics of lung cancer patients with COPD. We performed a retrospective cohort study that included 435 patients with pathologically confirmed lung cancer at the Ruijin Hospital. For patients with documented spirometry, Global Initiative for Chronic Obstructive Lung Disease criteria were used to define COPD. For patients without documented spirometry, chest computed tomography and other clinical information were used to define COPD. Tumor tissue DNA was extracted from formalin-fixed paraffin-embedded samples. DNA mutation analysis, multiplex immunohistochemistry (mIHC), calculation of tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), and predication of neoantigens were performed. Although SNV mutations in lung cancer patients with COPD (G1 group) were generally higher than those in lung cancer patients without COPD (G2 group), the difference in the number of mutations was insignificant between the two groups. Of the 35 mutated genes, the number of them was higher in G1 than in G2, except that of EGFR. PI3K-Akt signaling pathway was enriched from significantly different genes. While TMB and MATH levels were not significantly different, the tumor neoantigen burdenwas markedly higher in G1 than that in G2. The level of CD68+ macrophages was significant higher in the stroma and total areas in the G1 group than in G2 group. The level of CD8+ lymphocytes was markedly higher in the stroma and showed a clear tendency forhigher expression in the G1 group than inthe G2 group. No significant differences were observed for the level of programmed death-ligand 1+ (PD-L1+), programmed death 1+ (PD-1+), and CD68PD-L1 in the stroma, tumor and total areas. Our study revealed different genetic aberrations and pathways, higher neoantigen burden, and higher level of CD68+ macrophages and CD8+ T lymphocytes in lung cancer patients with COPD. Our investigation implies that the existence of COPD should be considered and immunotherapy is a potential choice when treating lung cancer patients with COPD.

Deep learning tumor heterogeneity metric from histopathology images vs next generation sequencing-derived scores for colon cancer prognostication.

3537 Background: Tumor heterogeneity is as an important determinant of clinical behavior in many cancer types, with increased heterogeneity thought to confer inferior clinical outcome. Sequencing based assessment of colon cancer has been used to quantify tumor heterogeneity and correlate it with survival, but is sensitive to the mutation calling algorithm utilized. Digitization of histopathology slides allows application of deep learning methods for image analysis. Automated slide annotation and feature extraction provides numeric representations of underlying phenotype from which tumor heterogeneity can be estimated. Here we compare the ability of a deep-learning tumor heterogeneity score (THS) to estimate overall survival in colon cancer patients to estimates produced by bulk sequencing derived mutant-allele tumor heterogeneity (MATH) and copy number variation (CNV) event scores. Methods: Digitized whole slide images (WSIs) from The Cancer Genome Atlas (TCGA) colon adenocarcinoma dataset are processed in a computational pipeline for tissue detection, numerical feature extraction, and cell type classification. WSIs are tiled and local THS calculated from imaging features. Corresponding MATH and CNV derived heterogeneity metrics are calculated from published sequencing data. Kaplan Meier curves are used to compare patient survival stratified by tumor heterogeneity as calculated by the three independent methods. Automated regional annotation identifies intra-tumoral and tumor-stromal boundary tiles and tumor THS is correlated to distance from the boundary. Results: Images from 379 patients (209 right-sided, 152 left-sided tumors) yielded 575,762 tiles. Automated annotation resulted in 272,791 intra-tumoral and 11,340 tumor-stromal boundary tiles. Stratification by imaging derived THS provided significant separation of overall survival curves (p &lt; .01) in contrast to MATH and CNV methods (p &gt; .05 for both). THS significantly separated the curves in right- but not left-sided cancers (p = .03 and .44, respectively). Evaluating THS as a function of distance from the tumor-stromal boundary, right-sided tumors showed significant decrease in THS with increasing distance from tumor edge. Conclusions: Our novel pipeline produced spatially resolved imaging data informed by underlying tumor phenotype without need for pathologist annotation. The resultant THS correlated with outcome and outperformed sequencing-based prognostication methods. The spatial information identified higher heterogeneity at the tumor edge than interior regions of right-sided, but not left-sided tumors, capturing known but poorly understood differences in colon tumors by location. Deep learning image analysis provided reproducible and cost-effective data with great potential both in clinical biomarker discovery and as a research tool.

Intratumoral heterogeneity as a predictive biomarker in immunotherapy for advanced head and neck squamous cell carcinoma.

e18028 Background: Intratumoral heterogeneity (ITH) is associated with the poor prognosis in a variety of solid tumors, because of the therapeutic failure and drug resistance. However, we still lack understanding of the relationship between ITH and immunotherapy for advanced head and neck squamous cell carcinoma (HNSCC). Methods: We used the Bioconductor R package Maftools to analyze somatic variants of HNSCC from MSK-IMPACT-1611 study cohort (PMID: 30643254) with data from 68 patients. Then, a mutant-allele tumor heterogeneity (MATH) algorithm was used to measure ITH score. Finally, we analyzed the difference in the genomes, and the association with tumor mutational burden (TMB) between the ITH score high (ITH-H) and ITH score low (ITH-L) groups, and the effect of ITH on the prognosis of immunotherapy. Results: There was no significant difference in the high frequency mutated genes between the high ITH and low ITH groups. The genes with the highest mutation frequency in ITH-H group were TP53 (90.48%), TERT (47.62%), CDKN2A (38.1%), FAT1 (33.33%), NOTCH1 (28.57%), KMT2D (19.05%), APC (14.29%), and ASXL1 (14.29%), while the genes with the highest mutation frequency in ITH-L group were TP53 (44.68%), PIK3CA (38.3%), TRET (36.17%), FAT1 (21.28%), NOTCH1 (19.15%), KMT2C (17.02%), KMT2D (17.02%), and CDKN2A (14.89%). The median overall survival (mOS) of ITH-L group was significantly higher than that of ITH-H group (not reach versus 10 months, hazard ratio (HR) = 2.15, 95%CI 1.05−4.4, P = 0.032). There was no significant difference in median TMB levels between ITH-L and ITH-H groups (P = 0.55). The TMB high (TMB-H) patients had no significantly better mOS than the TMB low (TMB-L) group (HR = 0.54, 95%CI 0.25−1.16, P = 0.11). A pooled analysis of ITH and TMB show that the ITH-L+TMB-H group had significantly better improvement mOS than that in the ITH-L+TMB-L, ITH-H+TMB-H, and ITH-H+TMB-L group (HR = 0.71, 95%CI 0.13−1.35, P = 0.048). Conclusions: ITH may serve as a positive predictor of immunotherapy in patients with advanced HNSCC and is independent of TMB.

Genomic landscape of locally advanced rectal adenocarcinoma: Comparison between before and after neoadjuvant chemoradiation and effects of genetic biomarkers on clinical outcomes and tumor response.

To explore genomic biomarkers in rectal cancer by performing whole-exome sequencing. Pre-chemoradiation (CRT) biopsy and post-CRT surgical specimens were obtained from 27 patients undergoing neoadjuvant CRT followed by definitive resection. Exomes were sequenced to a mean coverage of 30×. Somatic single-nucleotide variants (SNVs) and insertions/deletions (indels) were identified. Tumor mutational burden was defined as the number of SNVs or indels. Mutational signatures were extracted and fitted to COSMIC reference signatures. Tumor heterogeneity was quantified with a mutant-allele tumor heterogeneity (MATH) score. Genetic biomarkers and frequently occurred copy number alterations (CNAs) were compared between pre- and post-CRT specimens. Their associations with tumor regression grade (TRG) and clinical outcomes were explored. Top five mutated genes were APC, TP53, NF1, KRAS, and NOTCH1 for pre-CRT samples and APC, TP53, NF1, CREBBP, and ATM for post-CRT samples. Several gene mutations including RUNX1, EGFR, and TP53 in pre-CRT samples showed significant association with clinical outcomes, but not with TRG. However, no such association was found in post-CRT samples. Discordance of driver mutation status was found between pre- and post-CRT samples. In tumor mutational burden analysis, higher number of SNVs or indels was associated with worse treatment outcomes. Six single-base substitution (SBS) signatures identified were SBS1, SBS30, SBS29, SBS49, SBS3, and SBS44. The MATH score decreased after CRT on paired analysis. Less than half of CNAs frequent in post-CRT samples were present in pre-CRT samples. Pre- and post-CRT samples showed different genomic landscape. Potential genetic biomarkers of pre-CRT samples found in the current analysis call for external validation.

Intratumoral heterogeneity as a predictive biomarker in immunotherapy for advanced esophageal cancer.

e16059 Background: Previous studies have shown that the acquired resistance to anti-cancer therapy is largely due to intratumoral heterogeneity (ITH), thus leading to unfavourable prognosis. As known, there is no comprehensive research using ITH as a biomarker to predict the efficacy of immunotherapy in advanced esophageal cancer (ESCA) patients. Methods: Bioconductor R package Maftools was used to analyze somatic variants of advanced ESCA from MSK-IMPACT-1611 study cohort (PMID: 30643254) with data from 39 patients. We then used a mutant-allele tumor heterogeneity (MATH) algorithm to measure ITH score and analyzed the difference in the genetic profile between the ITH score high (ITH-H) and ITH score low (ITH-L) groups, the association with tumor mutational burden (TMB), and the effect of ITH on the prognosis of immunotherapy. Results: There were significant differences in gene mutation spectrum between ITH-H and ITH-L groups. The genes with the highest mutation frequency in ITH-H group were TP53 (93.75%), CDKN2A (37.5%), PREX2 (31.25%), PTPRD (25%), ALK (18.75%), ERBB4 (18.75%), and KMT2D (18.75%), while the genes with the highest mutation frequency in ITH-L group were TP53 (69.57%), CDKN2A (21.74%), PIK3CA (21.74%), APC (17.39%), ARID1A (17.39%), LATS1 (17.39%), and RNF43 (17.39%).There was significant difference in median overall survival (mOS) between ITH-L and ITH-H groups (not reach versus 5 months, hazard ratio (HR) = 3.96, 95%CI 1.02−15.39, P = 0.034). There was no significant difference in median TMB levels between ITH-L and ITH-H groups (7 Muts/Mb versus 8 Muts/Mb, P = 0.09). The TMB high (TMB-H) patients had no significantly better mOS than the TMB low (TMB-L) group (HR = 0.27, 95%CI 0.06−1.26, P = 0.072). A pooled analysis of ITH and TMB show that mOS in the ITH-L+ TMB-H group was significantly better than that in the ITH-L+TMB-L, ITH-H+TMB-H, and ITH-H+TMB-L group (HR = 2.03, 95%CI 0.06−7.69, P = 0.002). Conclusions: The results suggest ITH is a predictor of ESCA immunotherapy efficacy independent of TMB.

Intratumoral heterogeneity as a predictive biomarker in immunotherapy for advanced bladder cancer.

e16619 Background: Previous studies have shown that intra-tumor heterogeneity (ITH) can lead to drug resistance to tumor therapy, which is associated with poor prognosis of solid tumors. However, studies on the correlation between ITH and immunotherapy efficacy in patients with advanced bladder cancer (BLCA) are still lacking. Methods: Bioconductor R package Maftools was used to analyze somatic variants of advanced BLCA from an independent cohort (Miao-249 study cohort, PMID: 30150660) with data from 27 patients who underwent whole-exome sequencing. The ITH score was measured using the mutant-allele tumor heterogeneity (MATH) algorithm to analyze the difference in the genetic profile between the ITH score high (ITH-H) and ITH score low (ITH-L) groups, its association with tumor mutational burden (TMB), and the effect of ITH on the prognosis of immunotherapy. Results: There were significant differences in gene mutation spectrum between ITH-H and ITH-L groups. The genes with the highest mutation frequency in ITH-H group were TP53 (57.14%), DNAH5 (38.1%), TNRC18 (38.1%), TTN (38.1%), CSMD3 (33.33%), MDN1 (33.33%), MRPL49 (33.33%), and MUC19 (33.33%), while the genes with the highest mutation frequency in ITH-L group were KDM6A (83.33%), TP53 (66.67%), CALN1 (50%), MICAL2 (50%), MTOR (50%), NINL (50%), PCDHA (50%), and RMIBP2 (50%). The objective response rate (ORR) of immunotherapy was 66.66% and 42.86% for the patients with ITH-L and ITH-H subgroup. The ITH-L patients had significantly improved median overall survival (mOS) than the ITH-H group (not reach versus 12.3 months, hazard ratio (HR) = 6.65, 95%CI 0.86−51.36, P = 0.037). There was no significant difference in median TMB levels between ITH-L and ITH-H groups (8 Muts/Mb versus 7.6 Muts/Mb, P = 0.97). The TMB high (TMB-H) patients had no significantly better mOS than the TMB low (TMB-L) group (not reach versus 9.07 months, HR = 0.33, 95%CI 0.07−1.49, P = 0.13). A pooled analysis of ITH and TMB show that mOS in the ITH-L+ TMB-H group was numerically better than that in the ITH-H+TMB-H, ITH-H+TMB-L, and ITH-L+TMB-L group (not reach versus 15.6 months versus 7.1 months versus not reach, HR-1.57, 95CI 0−Inf, P = 0.1). Conclusions: The results suggest that ITH may be independent of TMB and a positive predictor of immunotherapy in patients with advanced BLCA.