Microsatellite Instability Score Research Articles

Stimulator of interferon genes mediated immune senescence reveals the immune microenvironment and prognostic characteristics of bladder cancer

BackgroundStudies have shown that the stimulator of interferon genes (STING) is critical in tumorigenesis, and development. This study aimed to investigate the immune profile and prognostic significance of STING-mediated immune senescence in bladder cancer (BLCA). MethodsWe identified differential genes between tumor and normal tissue based on the Cancer Genome Atlas database, and used consensus clustering to identify BLCA subtypes. The genes most associated with overall survival were screened by further analysis and used to construct risk models. Then, comparing the immune microenvironment, tumor mutational load (TMB), and microsatellite instability (MSI) scores between different risk groups. Eventually, a nomogram was constructed based on clinical information and risk scores. The model was validated using receiver operating curves (ROC) and calibration plots. ResultsWe identified 160 differential genes, including 13 genes most associated with prognosis. Three subtypes of bladder cancer with different clinical and immunological features were identified. Immunotherapy was more likely to benefit the low-risk group, which had higher TMB and MSI scores. The nomogram was found to be highly predictive based on ROC analysis and calibration plots. ConclusionThe risk model and nomogram not only predict the prognosis of BLCA patients but also can guide the treatment.

TET1 is a Diagnostic and Prognostic Biomarker Associated with Immune Infiltration in Papillary Thyroid Cancer.

To investigate the function of ten-eleven translocation 1 (TET1) and its underlying mechanism in papillary thyroid cancer (PTC). Using the RNA-Seq data based on GDC TCGA, we analyzed the gene expression pattern of TET1 in PTC. Immunohistochemistry was carried out to assess the TET1 protein level. Then, its diagnostic and prognostic functions were determined by various bioinformatics approaches. Enrichment analysis was performed to explore the potential pathways in which TET1 is mainly involved. Finally, the immune cell infiltration analysis was conducted and the association of TET1 mRNA expression with the expression levels of immune checkpoints, tumor mutation burden (TMB) score, microsatellite instability (MSI) score, and cancer stem cells (CSC) score was examined. TET1 expression was lower in PTC tissues compared with that in normal tissues (P < 0.01). Besides, TET1 had a certain value in diagnosing PTC, and low-TET1 mRNA expression led to favorable disease-specific survival (DSS) (P < 0.01). The enrichment analysis revealed autoimmune thyroid disease and cytokine-cytokine receptor interaction were the consistent pathways in which TET1 participated. TET1 was negatively correlated with the Stromal score and Immune score. The different proportions of immune cell subtypes were observed between high- and low-TET1 expression groups. Interestingly, TET1 mRNA expression was inversely related to the expression levels of immune checkpoints, and TMB, MSI, and CSC scores. TET1 might be a robust diagnostic and prognostic biomarker for PTC. TET1 affected the DSS of PTC patients possibly through the regulation of immune-related pathways and tumor immunity.

Abstract 7560: Microsatellite instability (MSI) detection using flow-based sequencing

Abstract Background: Microsatellite instability (MSI) is an important genomic biomarker associated with various cancers and hereditary conditions. Accurate and efficient classification of MSI status is essential for diagnosis, prognosis, and treatment decisions. Different approaches for testing MSI have been presented in the literature, including NGS-based methods which either rely on comparison with a matched control sample, a set of reference control samples, or the reference genome (no control). In this study, we explore the feasibility of accurately identifying MSI status using the UG100 platform, which utilizes flow-based sequencing chemistry. Since MSI detection is typically based on long homopolymers, we examined here whether the flow-based sequencing data can be effectively used for MSI classification. Methods: We performed whole genome sequencing (WGS) on a cohort of 24 cell lines with known MSI status, as well as on 15 tumor tissue samples, encompassing various cancer types, including colon, lung, bladder, and endometrial cancer. To determine the MSI status, polyA/T homopolymer loci were considered. We measured the MSI status in these loci using two methods: 1) Counting short indel variants detected using somatic Deep Variant, in comparison with matched blood normal, and 2) a novel MSI score based on the difference of the polyA/T homopolymer length, in comparison to the reference genome. We assessed the ability to evaluate the score for the full sequenced coverage (~100X) as well as when limiting to exome boundaries, and when sampling down to 1X coverage. Results and Conclusions: We established the performance of the MSI score on the cell lines with known MSI status. The score was verified on cell line mixtures (simulating lower tumor purity) as well as on clinical samples from various tissue sources, including colon samples annotated as mismatch-repair deficient. We demonstrate the ability to use the cost-effective UG100 sequencing combined with the two methodologies to identify MSI-high samples in these scenarios. Citation Format: Gila Lithwick-Yanai, Hila Benjamin, Jorge Cano-Nistal, Shir Geisler, Ariel Jaimovich, Nika Iremadze, Dror Kessler, Ilya Soifer, Danit Lebanony, Keren Ben Simhon, Shlomit Gilad, Eti Meiri, Doron Lipson, Yosef E. Maruvka. Microsatellite instability (MSI) detection using flow-based sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7560.

Abstract 4924: Assessing microsatellite instability dominance in colorectal cancer phenotype: A multi-study initiative using multi-target transformers for genomic biomarker prediction

Abstract We used deep learning (DL) to predict multiple genetic biomarkers of colorectal cancer (CRC) from routine histopathology images, aiming to identify morphological changes associated with the mutational profile of tumors. A new Transformer-based prediction model was developed which can simultaneously predict multiple biomarkers from a single histopathology image. We compared the performance of the multi-target approach to conventional single-target models. We analyzed five patient cohorts from the Genetics and Epidemiology of CRC Consortium (GECCO) with colorectal cancer (N=1,385 patients). Our model was trained on an internal data set (N=739) to predict the presence of &amp;gt;200 genetic alterations, focusing on genes with non-silent mutations and mutational signatures, which were assessed using targeted sequencing. We used a 7-fold cross validation and validated the model on an independent, external data set (N=646). Morphological features of microsatellite instability (MSI) are detectable by DL models in histopathology images, making MSI a potential confounding factor. Thus, we also assessed whether our model can predict genetic alterations regardless of MSI status, or whether the model identifies the MSI phenotype. For the majority of biomarkers, the multi-target transformer reached a higher prediction performance as measured by the mean Area Under the Receiver Operating Characteristic (AUROC) Curve and lower standard deviation than single-target DL models. For the external validation set, the mean AUROC of the multi-target versus the single-target model was 0.78 (+/- 0.01) versus 0.72 (+/- 0.06) for BRAF mutations, 0.88 (+/- 0.01) versus 0.86 (+/- 0.03) for hypermutation status, 0.94 (+/- 0.01) versus 0.91 (+/- 0.02) for MSI, 0.86 (+/- 0.01) versus 0.80 (+/- 0.05) for RNF43 mutations and 0.72 (+/- 0.02) versus 0.69 (+/- 0.05) for TP53 mutations, respectively. However, our analysis of the individual prediction scores suggests that the model does not identify the phenotype of the alterations themselves. Instead, the model seems to determine the status of specific genetic alterations based on their correlation with MSI. Consequently, biomarkers which are associated with microsatellite stability have prediction scores negatively correlated with predicted MSI scores. Conversely, biomarkers which are associated with MSI have prediction scores positively correlated with predicted MSI scores. Our results demonstrate potential benefits of multi-target DL models in improving the predictive power and efficacy of histology-based biomarker extraction compared to single-target DL models. However, our results crucially highlight the importance of considering potential confounders, such as MSI status in CRC, and emphasize the need for extensive analysis beyond AUROC in studies focusing on DL-based biomarker detection. Citation Format: Marco Gustav, Marko van Treeck, Zunamys I. Carrero, Chiara M. Loeffler, Nic G. Reitsam, Bruno Märkl, Asier Rabasco Meneghetti, Lisa A. Boardman, Amy J. French, Ellen L. Goode, Andrea Gsur, Stefanie Brezina, Marc J. Gunter, Neil Murphy, Paul Limburg, Stephen Thibodeau, Sebastian Foersch, Robert Steinfelder, Tabitha Harrison, Ulrike Peters, Amanda Phipps, Jakob N. Kather. Assessing microsatellite instability dominance in colorectal cancer phenotype: A multi-study initiative using multi-target transformers for genomic biomarker prediction [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4924.

Abstract 6456: The utility of clinical sequencing in the diagnosis and treatment of soft tissue sarcomas; Real world data based on nation-wide database

Abstract Purpose: Soft tissue sarcomas (STS) are rare and heterogeneous tumors arising from mesenchymal connective tissue, accounting for approximately 1%-2% of all malignancies. Due to their rarity and heterogeneity, it is challenging for accurate diagnosis, prognosis, and treatment of sarcoma. Recently, next-generation sequencing (NGS)-based comprehensive cancer genome profiling (CGP) has increasingly become a routine practice for patients with solid cancers worldwide. To collect genomic information and clinical characteristics of patients who underwent CGP, the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) has also been established since 2018 in Japan. Almost all the clinical and genomic data of patients who received CGP tests the had been collected in C-CAT. Here, we examined the utility of CGP test in the diagnosis and treatment of STS using this nation-wide database. Patients and Methods: We retrospectively evaluated the records of patients with STS who received F1CDx between 2019 and 2022 and registered in C-CAT. This assay carries 324 genes and determines nucleotide substitutions, insertions/deletions, and copy number (CN) alterations of 309 genes, fusions of 36 genes, tumor mutation burden (TMB) and microsatellite instability (MSI). High TMB (TMB-H) was defined as a TMB value &amp;gt;10 muts/Mb. Ranges of the MSI score were assigned MSI-High (MSI-H) or microsatellite stable (MSS). Results: From 2019 to 2022, 1387 patients with STS were registered in C-CAT. The histological types included leiomyosarcoma in 357 patients, dedifferentiated liposarcoma in 178 patients, and undifferentiated pleomorphic sarcoma in 82 patients, and the others. The most commonly altered genes included TP53, CDKN2A, Rb1, and CDKN2B. Among the 1387 cases, we observed 110 fusion events in 108 cases (7.7%), and 2 cases showed 2 types of fusion transcripts. Fifteen (2.8%) patients were re-classified based on the detection of highly histology-specific translocations. Among them, an initial diagnosis of sarcoma NOS was classified as Ewing Sarcoma (EWSR1-FLI1 in 2 patients), NTRK-rearranged spindle cell neoplasm (NTRK fusion in 3 patients), CIC-rearranged sarcoma (CIC-DUX4 in 3 patients), and sarcoma with BCOR genetic alterations (BCOR-ZC3H7B in 1 patient) as these gene fusions were identified. Druggable gene alterations was detected in 347 patients (25%) and 55 patients (4%) who received genotype-matched therapy. In 38 patients for whom the effect of treatment could be evaluated, complete response and partial response were achieved in 2 (5%) and 10 (26%) patients, respectively. Discussion: In conclusion, the comprehensive genomic profiling test appears to be an important tool in the diagnosis and treatment of sarcomas. Citation Format: Eiji Nakada, Tomohiro Fujiwara, Toshi Kunisada, Shota Takihira, Daisuke Ennishi, Hideki Yamamoto, Kiichiro Ninomiya, Shuta Tomida, Mashu Futagawa, Akira Hirasawa, Shinichi Toyooka, Toshifumi Ozaki. The utility of clinical sequencing in the diagnosis and treatment of soft tissue sarcomas; Real world data based on nation-wide database [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6456.

Phase II study of nivolumab in patients with genetic alterations in DNA damage repair and response who progressed after standard treatment for metastatic solid cancers (KM-06)

BackgroundImmune-modulating antibodies targeting programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) have demonstrated promising antitumor efficacy in various types of cancers, especially highly mutated ones. Genetic alterations in DNA damage...

Multi-omics and single-cell sequencing analyses reveal the potential significance of circadian pathways in cancer therapy

ABSTRACT Background Circadian rhythm disturbance is an independent risk factor for cancer. However, few studies have been reported on circadian rhythm related genes (CRGs) in cancer, so it is important to further explore the impact of CRGs in pan-cancer. Research design and methods The Cancer Genome Atlas database was used to collect cancer-related data such as copy number variation, single nucleotide variants, methylation, and survival differences. Immunohistochemistry (IHC) was used to verify the expression of circadian rhythm hub genes. The circadian pathway scores (CRS) were calculated using single-sample gene enrichment analysis. TIMER and GEPIA databases were used for immune-cell integration and assessment. Single-cell sequencing data was used to evaluate the abundance of CRS in tumor microenvironment cells. Results In this study, we found that the expression of circadian pathway varies between tumors. CSNK1E was significantly up-regulated in most tumors and CRY2 was significantly down-regulated in most tumors. The protein interaction network suggested CRY2 as the core gene and IHC verified its significant low expression in KIRC. In addition, CRGs were found to be protective factors in most tumors and have the potential to act as specific immune markers in different tumors. CRS was significantly lower in abundance in most tumors. CRS was significantly associated with overall survival in tumor patients and associated with the expression of many immune cells in the tumor immune microenvironment. CRS is significantly associated with tumor mutational burden and microsatellite instability scores in most tumors and may serve as a potential immunotherapeutic marker. Conclusions The circadian rhythm pathway may be a breakthrough point in regulating the tumor microenvironment meanwhile a suitable immunotherapy method in the future.

Race, Prevalence of POLE and POLD1 Alterations, and Survival Among Patients With Endometrial Cancer.

Black patients with endometrial cancer (EC) in the United States have higher mortality than patients of other races with EC. The prevalence of POLE and POLD1 pathogenic alterations in patients of different races with EC are not well studied. To explore the prevalence of and outcomes associated with POLE and POLD1 alterations in differential racial groups. This retrospective cohort study incorporated the largest available data set of patients with EC, including American Association for Cancer Research Project GENIE (Genomics Evidence Neoplasia Information Exchange; 5087 participants), Memorial Sloan Kettering-Metastatic Events and Tropisms (1315 participants), and the Cancer Genome Atlas Uterine Corpus Endometrial Carcinoma (517 participants), collected from 2015 to 2023, 2013 to 2021, and 2006 to 2012, respectively. The prevalence of and outcomes associated with POLE or POLD1 alterations in EC were evaluated across self-reported racial groups. Patients of different racial groups with EC and with or without POLE or POLD1 alterations. The main outcome was overall survival. Data on demographic characteristics, POLE and POLD1 alteration status, histologic subtype, tumor mutation burden, fraction of genome altered, and microsatellite instability score were collected. A total of 6919 EC cases were studied, of whom 444 (6.4%), 694 (10.0%), and 4869 (70.4%) patients were self-described as Asian, Black, and White, respectively. Within these large data sets, Black patients with EC exhibited a lower weighted average prevalence of pathogenic POLE alterations (0.5% [3 of 590 cases]) compared with Asian (6.1% [26 of 424]) or White (4.6% [204 of 4520]) patients. By contrast, the prevalence of POLD1 pathogenic alterations was 5.0% (21 cases), 3.2% (19 cases), and 5.6% (255 cases) in Asian, Black, and White patients with EC, respectively. Patients with POLD1 alterations had better outcomes regardless of race, histology, and TP53 alteration status. For a total of 241 clinically annotated Black patients with EC, a composite biomarker panel of either POLD1 or POLE alterations identified 7.1% (17 patients) with positive outcomes (1 event at 70 months follow up) in the small sample of available patients. In this retrospective clinicopathological study of patients of different racial groups with EC, a composite biomarker panel of either POLD1 or POLE alteration could potentially guide treatment de-escalation, which is especially relevant for Black patients.

Comprehensive characterization of PKHD1 mutation in human colon cancer.

The PKHD1 (Polycystic Kidney and Hepatic Disease 1) gene is essential for producing fibrocystin or polyductin, which is crucial in various cellular functions. Mutations in PKHD1 have been found to be involved in the development and progression of colorectal cancer (CRC). Along with APC, TP53, and KRAS, PKHD1 is one of the most frequently mutated genes in CRC. PKHD1 expression is governed by the Wnt/PCP pathway, often dysregulated in CRC. Targeting this pathway, crucial for CRC progression, could unveil potential therapeutic strategies for colon cancer treatment. This study examined an in-house dataset of 3702 colon cancer samples, analyzing mutation landscapes, clinical features, tumor mutational burden (TMB), microsatellite instability (MSI), and chromosomal instability (CIN) score. For the survival analysis of PKHD1 patients, survival data of 436 colon adenocarcinoma samples were obtained from TCGA dataset. Additionally, 433 samples from TCGA with RNA-seq data were used for the assessment of immune cell infiltration and gene set enrichment analysis. Polycystic Kidney and Hepatic Disease 1 mutation was detected in 424 colon cancer patients from our in-house cohort and was associated with increased TMB, higher MSI, and lower CIN score. Importantly, within the TCGA dataset, PKHD1 mutations were identified as an independent prognostic factor, not merely correlated with established prognostic biomarkers, and were associated with poorer overall survival outcomes. In terms of immune response, these mutations correlated with increased enrichment scores for 12 immune cell types, including B cell plasma, macrophages, and naive CD4+ T cells. Additionally, interferon alpha and interferon-gamma gene sets were significantly down-regulated in patients with PKHD1 mutations (FDA q-value < 0.1). Overall, these findings suggest that PKHD1 may be a potential biomarker for the prognosis of colon cancer and provide some insight for personalized immunotherapy.

ASF1B acted as a prognostic biomarker for stomach adenocarcinoma.

Stomach adenocarcinoma (STAD) has a high mortality rate due to the lack of highly sensitive biomarkers. Therefore, the search for potential tumor markers is of great value. ASF1B is a prognostic marker for a variety of tumors, while the prognostic value and immune microenvironment of ASF1B in STAD remain unclear, and to be determined. Kaplan-Meier analysis was performed to analyze the prognostic role of ASF1B in STAD. Functional enrichment of ASF1B was explored with GO and KEGG pathway analysis. We also explored the correlation between ASF1B expression and immune infiltration in STAD. ASF1B was significantly upregulated in STAD tissues and high expression of ASF1B indicated a poor overall survival, progression-free survival, and first progression rate in STAD. The functional enrichment analysis of ASF1B and related genes showed high enrichment in the cell cycle and DNA repair, and the ASF1B high expression group was also mainly enriched in pathways such as the cell cycle. Analysis of tumor immune infiltration showed that ASF1B expression was significantly associated with the majority of immune cell infiltration in STAD. Moreover, STAD patients with high ASF1B expression had a higher tumor mutation burden score, microsatellite instability score, PD-1 immunophenoscore, and immune checkpoint expression. Our results suggest that ASF1B was an independent prognostic factor for STAD as well as a potential target for immunotherapy.

FANCD2 as a novel prognostic biomarker correlated with immune and drug therapy in Hepatitis B-related hepatocellular carcinoma

BackgroundFerroptosis is related to the immunosuppression of tumors and plays a critical role in cancer progression. Fanconi anemia complementation group D2 (FANCD2) is a vital gene that regulates ferroptosis. However, the mechanism of action of FANCD2 in Hepatitis B-related hepatocellular carcinoma (HCC) remains unknown. In this study, we investigated the prognostic significance and mechanism of action of FANCD2 in Hepatitis B-related HCC.MethodsThe expression of FANCD2 in Hepatitis B-related HCC was explored using The Cancer Genome Atlas (TCGA) and validated using the Gene Expression Omnibus (GEO) database. Univariate and multivariate Cox regression analyses and Kaplan–Meier survival curves were used to analyze the relationship between FANCD2 expression and the overall survival of patients with Hepatitis B-related HCC. Protein–protein interaction networks for FANCD2 were built using the STRING website. In addition, correlations between FANCD2 expression and the dryness index, tumor mutational burden, microsatellite instability (MSI), immune pathways, genes involved in iron metabolism, and sorafenib chemotherapeutic response were analyzed.ResultsOur results indicated that FANCD2 was significantly overexpressed in Hepatitis B-related HCC and demonstrated a strong predictive ability for diagnosis (Area Under Curve, 0.903) and prognosis of the disease. High FANCD2 expression was associated with poor prognosis, high-grade tumors, high expression of PDL-1, high MSI scores, and low sorafenib IC50 in Hepatitis B-related HCC. BRCA1, BRCA2, FAN1, and FANCC were vital proteins interacting with FANCD2. The expression level of FANCD2 significantly correlated with the infiltration levels of Treg cells, B cells, CD8 + T cells, CD4 + T cells, neutrophils, macrophages, myeloid dendritic cells, and NK cells in Hepatitis B-related HCC. FANCD2 was positively correlated with the tumor proliferation signature pathway, DNA repair, and cellular response to hypoxia.ConclusionOur study indicated that FANCD2 was a potential novel biomarker and immunotherapeutic target against Hepatitis B-related HCC, which might be related to the chemotherapeutic response to sorafenib.

Prognostic and tumor microenvironmental feature of clear cell renal cell carcinoma revealed by m6A and lactylation modification-related genes.

Both lactylation and m6A modification have important implications for the development of clear cell renal cell carcinoma (ccRCC), and we aimed to use crosstalk genes of both to reveal the prognostic and immunological features of ccRCC. Our first step was to look for lactylation-related genes that differed between normal and tumor tissues, and then by correlation analysis, we found the genes associated with M6A. Following that, ccRCC subtypes will be identified and risk models will be constructed to compare the prognosis and tumor microenvironment among different subgroups. A nomogram was constructed to predict the prognosis of ccRCC, and in vitro, experiments were conducted to validate the expression and function of key genes. We screened 100 crosstalk genes and identified 2 ccRCC subtypes. A total of 11 prognostic genes were screened for building a risk model. we observed higher immune scores, elevated tumor mutational burden, and microsatellite instability scores in the high-risk group. Therefore, individuals classified as high-risk would derive greater benefits from immunotherapy. The nomogram's ability to predict overall survival with a 1-year AUC of 0.863 demonstrates its significant practical utility. In addition, HIBCH was identified as a potential therapeutic target and its expression and function were verified by in vitro experiments. In addition to developing a precise prognostic nomogram for patients with ccRCC, our study also discovered the potential of HIBCH as a biomarker for the disease.

A novel prognostic signature based on immunogenic cell death score predicts outcomes and response to transcatheter arterial chemoembolization and immunotherapy in hepatocellular carcinoma.

The phenomenon of immunogenic cell death (ICD) is intricately linked to numerous antitumor treatments and exerts a profound regulatory function in the tumor immune microenvironment (TIME). We aimed to establish a prognostic signature from the ICD-related biomarkers to differentiate the TIME in hepatocellular carcinoma and predict diverse outcomes for patients with liver cancer. ICD score-related genes (ICDSGs) were identified using the weighted gene co-expression network analysis (WGCNA). The ICD score-related signature (ICDSsig) was established by applying LASSO and Cox regression. Model precision was verified using the external datasets. We used independent prognostic variables in clinicopathologic factors to develop a nomogram. Further, clinical characteristics, immune and molecular landscapes, the responses of transcatheter arterial chemoembolization (TACE) and immunotherapy, and chemotherapy sensitivity were analyzed for high- and low-risk patients. ICD score-calculated using the single-sample gene set enrichment analysis (ssGSEA)-displayed strong associations with the TIME in HCC. We identified 34 ICDSGs after integrating the TCGA and GSE104580 datasets. Then, three novel ICDSGs (DNASE1L3, KLRB1, and LILRB1) were screened out to construct the ICDSsig; the prognostic signature performed well in the external databases. The high-risk patients had worse outcomes owing to their advanced pathological state, non-response of TACE, and immune-cold phenotype in the immune landscapes. The immune checkpoint genes, N6-methyladenosine-relevant genes, and microsatellite instability score were increased in the high-risk subgroup, thereby indicating a favorable sensitivity to immunotherapy. Common chemotherapy drugs were more effective in high-risk patients due to low half-maximal inhibitory concentration values. The ICDSsig can potentially predict outcomes and therapeutic responses for patients with liver cancer and may assist clinicians in designing individualized treatment strategies.

A multi-omics analysis reveals CLSPN is associated with prognosis, immune microenvironment and drug resistance in cancers

BackgroundImmunotherapy is effective only in limited patients. It is urgent to discover a novel biomarker to predict immune cells infiltration status and immunotherapy response of different cancers. CLSPN has been reported to play a pivotal role in various biological processes. However, a comprehensive analysis of CLSPN in cancers has not been conducted.MethodsTo show the whole picture of CLSPN in cancers, a pan-cancer analysis was conducted in 9125 tumor samples across 33 cancer types by integrating transcriptomic, epigenomic and pharmacogenomics data. Moreover, the role of CLSPN in cancer was validated by CCK-8, EDU, colony formation and flow cytometry in vitro and tumor cell derived xenograft model in vivo.ResultsCLSPN expression was generally upregulated in most cancer types and was significantly associated with prognosis in different tumor samples. Moreover, elevated CLSPN expression was closely correlated with immune cells infiltration, TMB (tumor mutational burden), MSI (microsatellite instability), MMR (mismatch repair), DNA methylation and stemness score across 33 cancer types. Enrichment analysis of functional genes revealed that CLSPN participated in the regulation of numerous signaling pathways involved in cell cycle and inflammatory response. The expression of CLSPN in LUAD patients were further analyzed at the single-cell level. Knockdown CLSPN significantly inhibited cancer cell proliferation and cell cycle related cyclin-dependent kinase (CDK) family and Cyclin family expression in LUAD (lung adenocarcinoma) both in vitro and in vivo experiments. Finally, we conducted structure-based virtual screening by modelling the structure of CHK1 kinase domain and Claspin phosphopeptide complex. The top five hit compounds were screened and validated by molecular docking and Connectivity Map (CMap) analysis.ConclusionOur multi-omics analysis offers a systematic understanding of the roles of CLSPN in pan-cancer and provides a potential target for future cancer treatment.

Based on disulfidptosis, revealing the prognostic and immunological characteristics of renal cell carcinoma with tumor thrombus of vena cava and identifying potential therapeutic target AJAP1.

Patients with clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus have a poor prognosis, high surgical risk, and lack of targeted therapeutic agents. Genes with consistent differential expression trends in tumor tissues and VTT groups were first screened, and then differential genes associated with disulfidptosis were found by correlation analysis. Subsequently, identifying ccRCC subtypes and constructing risk models to compare the differences in prognosis and the tumor microenvironment in different subgroups. Finally, constructing a nomogram to predict the prognosis of ccRCC and validate key gene expression levels in cells and tissues. We screened 35 differential genes related to disulfidptosis and identified 4 ccRCC subtypes. Risk models were constructed based on the 13 genes, and the high-risk group had a higher abundance of immune cell infiltration, tumor mutational load, and microsatellite instability scores, predicting high sensitivity to immunotherapy. The 1-year AUC = 0.869 for predicting OS by nomogram has a high application value. The expression level of the key gene AJAP1 was low in both tumor cell lines and cancer tissues. Our study not only constructed an accurate prognostic nomogram for ccRCC patients but also identified an AJAP1 biomarker as a potential biomarker for the disease.

Mitochondrial metabolic reprogramming-mediated immunogenic cell death reveals immune and prognostic features of clear cell renal cell carcinoma.

Mitochondrial metabolic reprogramming (MMR)-mediated immunogenic cell death (ICD) is closely related to the tumor microenvironment (TME). Our purpose was to reveal the TME characteristics of clear cell renal cell carcinoma (ccRCC) by using them. Target genes were obtained by intersecting ccRCC differentially expressed genes (DEGs, tumor VS normal) with MMR and ICD-related genes. For the risk model, univariate COX regression and K-M survival analysis were used to identify genes most associated with overall survival (OS). Differences in the TME, function, tumor mutational load (TMB), and microsatellite instability (MSI) between high and low-risk groups were subsequently compared. Using risk scores and clinical variables, a nomogram was constructed. Predictive performance was evaluated by calibration plots and receiver operating characteristics (ROC). We screened 140 DEGs, including 12 prognostic genes for the construction of risk models. We found that the immune score, immune cell infiltration abundance, and TMB and MSI scores were higher in the high-risk group. Thus, high-risk populations would benefit more from immunotherapy. We also identified the three genes (CENPA, TIMP1, and MYCN) as potential therapeutic targets, of which MYCN is a novel biomarker. Additionally, the nomogram performed well in both TCGA (1-year AUC=0.862) and E-MTAB-1980 cohorts (1-year AUC=0.909). Our model and nomogram allow accurate prediction of patients' prognoses and immunotherapy responses.

Genomic and transcriptomic features between primary and paired metastatic fumarate hydratase–deficient renal cell carcinoma

BackgroundFumarate hydratase–deficient renal cell carcinoma (FH-RCC) is a rare highly aggressive subtype of kidney cancer for which the distinct genomic, transcriptomic, and evolutionary relationships between metastatic and primary lesions are still unclear.MethodsIn this study, whole-exome, RNA-seq, and DNA methylation sequencing were performed on primary-metastatic paired specimens from 19 FH-RCC cases, including 23 primary and 35 matched metastatic lesions. Phylogenetic and clonal evolutionary analyses were used to investigate the evolutionary characteristics of FH-RCC. Transcriptomic analyses, immunohistochemistry, and multiple immunofluorescence experiments were performed to identify the tumor microenvironmental features of metastatic lesions.ResultsPaired primary and metastatic lesions generally showed similar characteristics of tumor mutation burden, tumor neoantigen burden, microsatellite instability score, CNV burden, and genome instability index. Notably, we identified an FH-mutated founding MRCA (the most recent common ancestor) clone that dominated the early evolutionary trajectories in FH-RCC. Although both primary and metastatic lesions manifested high immunogenicity, metastatic lesions exhibited higher enrichment of T effector cells and immune-related chemokines, together with upregulation of PD-L1, TIGIT, and BTLA. In addition, we found that concurrent NF2 mutation may be associated with bone metastasis and upregulation of cell cycle signature in metastatic lesions. Furthermore, although in FH-RCC metastatic lesions in general shared similar CpG island methylator phenotype with primary lesions, we found metastatic lesions displaying hypomethylated chemokine and immune checkpoints related genomic loci.ConclusionsOverall, our study demonstrated the genomic, epigenomic, and transcriptomic features of metastatic lesions in FH-RCC and revealed their early evolutionary trajectory. These results provided multi-omics evidence portraying the progression of FH-RCC.

Abstract 3379: Comprehensive circulating tumor DNA and CTC profiling of treatment naïve early-stage head and neck cancer patients reveals early signature of disease progression

Abstract Comprehensive CtDNA and CTC profiling of treatment naïve early-stage head and neck cancer patients reveals early signatures of disease progressionBackground: We performed comprehensive ctDNA analysis on early-stage HNC patients in a pilot study to determine the mutational landscape in HNC patients with a known tobacco history. Methods: We analysed ctDNA of 18 early-stage HNC patients for genomic landscapes using the illumina NextSeq 2000 NGS. A custom-designed OncoIndex gene panel was used for the hybrid capture target-enrichment of critical cancer genes. Panel was designed to detect cancer targeting exonic sequence of 600 genes reporting SNVs and indels along fusions and copy number amplification. The gene panel detected genome-wide signatures including bTMB, MSI (microsatellite instability), HRD (homologous recombination deficiency) prediction and calculate cfDNA tumor fraction. Results: 80 % patients showed presence of at least one CTC in peripheral blood, possibly indicating the progressive disease at the time of presentation. Comprehensive genomic profile obtained from plasma cfDNA of early-stage HNC cancer patients predominantly had low bTMB and MSI Scores (99 % patients). However, HRD and LOH matrix was high for 60 % patients indicating highly dysregulated DNA repair activities. Concurring to these observations, 98 % patients had mutations in key tumor suppressor and DNA damage response (DDR) genes possibly resulting in their loss of function. Besides DNA damage pathway, 60% patients harboured alterations in RTK genes including FGFR, EGFR and PDEGFR family and 32% patients showed activating mutations in Erk1 and its upstream regulators. MSH2 was the most prominently mutated gene (37%) followed by FGFR (32%). Surprisingly, unlike HPV positive advanced HNC cases, TP53 mutations were not detected in any patient, though alterations in TS genes were most prevalent in the study population. 51% alterations resulted into truncated proteins possibly impairing their functions, while 42% alterations were point mutations, 6 % were frameshift and 1 % indels. Presence of mutations in BRAF, PDGFR, FGFR and KIT genes suggested for the potential therapy resistance. Tumor fraction representing ctDNA showed elevated range from 20 % to 45 % with a corresponding ploidy between 2 to 4. Conclusions: Comprehensive ctDNA profile showed major gene alterations in TS and DDR response pathway genes besides mutations in proliferative signaling members. TP53 mutation was not detected, although critical tumor suppressor and DDR genes were predominantly mutated, suggesting for a unique mutation pattern associated with early-stage HNC due to tobacco etiology. Our results suggest that comprehensive ctDNA analysis along CTC profiling can predict the disease progression beforehand and may offer new treatment options to early-stage HNC patients. Citation Format: Gowhar Shafi, Atul Bharde, Fauzul Moubeen, Kanchan Hariramani, Alain D’Souza, Trupti Kad, Bhagwat Jadhav, Sangita Prajapati, Aditi Rani, Madhura Basavalingegowda, Mohan Uttarwar, Gourishankar Aland, Sreeja Jayant, Aravindan Vasudevan, Pankaj Chaturvedi, Jayant Khandare. Comprehensive circulating tumor DNA and CTC profiling of treatment naïve early-stage head and neck cancer patients reveals early signature of disease progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3379.

Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome.

Background: Lung squamous cell carcinoma (LUSC) shares less typical onco-drivers and target resistance, but a high overall mutation rate and marked genomic complexity. Mismatch repair (MMR) deficiency leads to microsatellite instability (MSI) and genomic instability. MSI is not an ideal option for prognosis of LUSC, whereas its function deserves exploration. Method: MSI status was classified by MMR proteins using unsupervised clustering in the TCGA-LUSC dataset. The MSI score of each sample was determined by gene set variation analysis. Intersections of the differential expression genes and differential methylation probes were classified into functional modules by weighted gene co-expression network analysis. Least absolute shrinkage and selection operator regression and stepwise gene selection were performed for model downscaling. Results: Compared with the MSI-low (MSI-L) phenotype, MSI-high (MSI-H) displayed higher genomic instability. The MSI score was decreased from MSI-H to normal samples (MSI-H > MSI-L > normal). A total of 843 genes activated by hypomethylation and 430 genes silenced by hypermethylation in MSI-H tumors were classified into six functional modules. CCDC68, LYSMD1, RPS7, and CDK20 were used to construct MSI-related prognostic risk score (MSI-pRS). Low MSI-pRS was a protective prognostic factor in all cohorts (HR = 0.46, 0.47, 0.37; p-value = 7.57e-06, 0.009, 0.021). The model contains tumor stage, age, and MSI-pRS that showed good discrimination and calibration. Decision curve analyses indicated that microsatellite instability-related prognostic risk score added extra value to the prognosis. A low MSI-pRS was negatively correlated with genomic instability. LUSC with low MSI-pRS was associated with increased genomic instability and cold immunophenotype. Conclusion: MSI-pRS is a promising prognostic biomarker in LUSC as the substitute of MSI. Moreover, we first declared that LYSMD1 contributed to genomic instability of LUSC. Our findings provided new insights in the biomarker finder of LUSC.

Estrogen-related genes influence immune cell infiltration and immunotherapy response in Hepatocellular Carcinoma.

Immunotherapy has been the first-line treatment option in advanced Hepatocellular Carcinoma(HCC); but now, there are no established molecular markers that can predict immunotherapy response. Estrogen has a crucial role in the development of a variety of liver illnesses, including liver fibrosis, Nonalcoholic fatty liver disease (NAFLD), and HCC. Nonetheless, the significance of estrogen-related genes in HCC immunotherapy and the underlying molecular mechanisms are not yet fully understood. In this study, we constructed a novel estrogen-related gene prognostic signature (ERGPS) by analyzing bulk RNA sequencing data from 365 HCC patients. Based on the median risk score, we divided 365 HCC patients into low- and high-risk groups. Tumor mutation burden (TMB), Microsatellite instability (MSI), T cell receptor (TCR) richness, B cell receptor (BCR) richness, single-nucleotide variants (SNV) Neoantigens, Cancer Testicular Antigens (CTA) scores, and Tumour Immune Dysfunction and Exclusion (TIDE) scores were used to evaluate the magnitude of immunotherapy response. Multiple external datasets validate the validity and robustness of the prognostic signature. Real-time quantitative polymerase chain reaction (qRT-PCR) was used to validate estrogen-related gene overexpression in HCC tissue samples. ERGPS is an independent risk factor affecting the prognosis of HCC patients and is superior to other clinical variables in predicting patient survival and immunotherapy response. Multiple independent external datasets confirmed the superior predictive efficacy of the prognostic signature. The prognostic signature was positively correlated with TMB score, MSI score, TCR richness, BCR richness, SNV Neoantigens score, CTA score, expression levels of immune checkpoint-related genes, and TIDE score. Patients with HCC in the high-risk group identified by the prognostic signature were likely to be more responsive to immunotherapy and more suitable for immunotherapy. qRT-PCR confirmed that estrogen-related genes of the construct signature were highly expressed in HCC tumor tissues. Estrogen-related genes are overexpressed in HCC tissues. Our novel prognostic signature can accurately predict not only the prognosis but also the immunotherapy response of HCC patients. In the future, prognostic signatures will be a useful tool for clinicians to screen patients with HCC who are suitable for immunotherapy.