Tumor Mutation Research Articles

Development and validation of disulfidptosis-related genes signature for patients with glioma

BackgroundDisulfidptosis has recently emerged as a novel form of regulated cell death (RCD). Evasion of cell death is a hallmark of cancer, and the resistance of many tumors to apoptosis-inducing therapies has heightened interest in exploring alternative RCD mechanisms.MethodsTranscriptomic and clinical data were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Chinese Glioma Genome Atlas (CGGA). Glioma samples were classified using non-negative matrix factorization (NMF). A predictive model was constructed using Lasso regression analysis, and its performance was evaluated through receiver operating characteristic (ROC) and Kaplan–Meier survival analyses. The relationship between the model and the tumor immune microenvironment (TIME) as well as treatment sensitivity was also assessed. Finally, we validated the expression of key signature genes in glioma.ResultsGlioma samples were categorized into two distinct subtypes based on disulfidptosis-related genes, showing significant differences in overall survival (OS) and progression-free survival (PFS) between the subtypes. A genetic risk score model was then developed using these genes. A nomogram predicting OS was constructed using the risk score and clinical variables. Patients were stratified into low- and high-risk groups based on the median risk score from the TCGA cohort. Low-risk patients had significantly better outcomes compared to high-risk patients (TCGA cohort, OS: p < 0.001; PFS: p < 0.001; CGGA cohort, OS: p < 0.001). The risk score was associated with HLA expression, immune checkpoint genes, immune cell infiltration, immune function, tumor mutation burden, tumor stemness score, and drug sensitivity. Lastly, the expression of 11 signature genes was confirmed in glioma tissues.ConclusionsThe disulfidptosis-related gene-based risk score model effectively predicted glioma outcomes and highlighted the role of disulfidptosis-related genes in tumor immunity. This study offers potential new avenues for glioma treatment by targeting disulfidptosis.

GG-NER’s role in androgen receptor signaling inhibitor response for advanced prostate cancer

BackgroundAdvanced prostate cancer (PCa) often initially responds to androgen receptor signaling inhibitors (ARSI) but frequently develops resistance, driven by tumor heterogeneity and therapeutic pressure. Addressing the clinical challenge of identifying non-responsive patients and discovering new therapeutic targets is urgently needed.MethodsWe utilized single-sample gene set enrichment analysis (ssGSEA) to elucidate the influence of the GG-NER pathway on ARSI response in PCa. We then constructed and validated a prognostic model based on this pathway using LASSO regression, Kaplan-Meier analysis, Cox regression, and ROC analysis. Additionally, we mapped tumor mutations to delineate the mutational landscapes across different risk groups and explored functional pathways through GO, KEGG, and GSEA analyses. The impact of the GG-NER pathway on enzalutamide sensitivity and DNA repair in PCa was further validated through CCK-8 assays, colony formation assays, in vivo experiments, and immunofluorescence.ResultsssGSEA indicated a trend of GG-NER pathway upregulation in patients with poor ARSI response. The GG-NER characteristic gene score (NECGS) identified a high-risk group with diminished ARSI response, serving as an independent prognostic indicator with strong predictive power. This high-risk group exhibited elevated TP53 mutation frequencies and significant enrichment in key pathways such as ribosome and mitochondrial functions, as well as MYC and E2F signaling. Experimental validation confirmed that targeting the GG-NER pathway or its key gene, ACTL6A, significantly reduces enzalutamide resistance in resistant cell lines and increases γH2AX expression.ConclusionNECGS effectively predicts ARSI response in PCa, and our comprehensive analysis underscores the critical role of the GG-NER pathway in enzalutamide resistance, positioning ACTL6A as a potential therapeutic target for PCa.

Analysis of transcriptomic data reveals the landscape of cholesterol metabolism in prostate cancer and impact of related signature on survival

BackgroundCholesterol metabolism is essential for the development and progression of prostate cancer (PCa). Our previous study provided a new insight of cholesterol metabolism in the systematic management of PCa. However, the comprehensive role of cholesterol metabolism in PCa remains unclear.MethodsUsing the cholesterol metabolism related genes (CMRGs) downloaded from the MSigDB database, and gene expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we constructed a cholesterol risk index by the least absolute shrinkage and selection operator (LASSO) model, and correlated the risk index with prognosis, tumor mutation burden (TMB), tumor microenvironment (TME) infiltration and response to chemotherapy and immunotherapy. RT-qPCR, western blot, immunohistochemistry, cell proliferation assays by CCK-8 and EdU assays, and cell apoptosis assays by flow cytometry analysis were also performed.ResultsWe found PCa was tightly correlated with the cholesterol metabolism pathways. The cholesterol risk index was an excellent and independent predictor of prognosis for PCa. A nomogram involving the risk index and other clinical factors (age, T stage) was established to explore the clinical value of risk index. We found high-risk index group was associated with worse prognosis, higher TMB, lower infiltration level of CD8+ T cells and a worse response to chemotherapy and immunotherapy. RT-qPCR, western blot and immunohistochemical staining validated the expression level of important CMRGs in PCa. In vitro experiments revealed downregulation of cholesterol metabolism could inhibit the proliferation of PCa cells and promoted their apoptosis.ConclusionsWe demonstrated the comprehensive role of cholesterol metabolism in PCa. Using the risk index, we could predict the prognosis, TME infiltration and response to chemotherapy/immunotherapy of PCa. Better understanding and evaluating the cholesterol metabolism could aid in precision medicine and promoting prognosis of PCa.

Continuous prediction for tumor mutation burden based on transcriptional data in gastrointestinal cancers

BackgroundTumor mutation burden (TMB) has been considered a biomarker for utilization of immune checkpoint inhibitors(ICIs), but whole exome sequencing(WES) and cancer gene panel(CGP) based on next generation sequencing for TMB detection are costly. Here, we use transcriptome data of TCGA to construct a model for TMB prediction in gastrointestinal tumors.MethodsTranscriptome data, somatic mutation data and clinical data of four gastrointestinal tumors from TCGA, including esophageal cancer (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD) and rectal adenocarcinoma (READ). Using R, we performed visual analysis of somatic mutation data, differentially expressed genes (DEGs) function enrichment analysis, gene set enrichment analysis (GSEA), and estimated TMB value in clinic. Finally, a deep neural network (DNN) model was constructed for TMB prediction.ResultsVisualization of somatic mutation data summarized the classification of mutation, frequency of each mutation type, and top-mutated genes. GSEA showed the enrichment of CD4+/CD8+ T cells in the high TMB group and the activation of tumor suppressing pathways. Single-sample GSEA (ssGSEA) manifested that the high-TMB group had higher level of multiple immune cells infiltration. In addition, distribution of TMB was related to clinical parameters.Like age, M stage, N stage, AJCC stage, and overall survival(OS). After model optimization using genetic algorithm, in the training set, validation set, and testing set, the Pearson relevance coefficient r between predicted values and actual values reaches 0.98, 0.82, and 0.92, respectively; the coefficient of determination R2 is 0.95, 0.82, and 0.7, respectively.ConclusionTMB correlates with clinicopathological parameters in gastrointestinal carcinoma, and patients with high TMB have higher levels of immune infiltration. In addition, the DNN model based on 31 genes predicts TMB of gastrointestinal tumors in a high accuracy.

Interferon-stimulated gene subtypes as key indicators of immune landscape and survival outcomes in ovarian cancer

PurposeOvarian cancer (OV) remains the most lethal gynecological malignancy, underscoring the critical need for robust prognostic biomarkers to enhance patient outcomes. In this study, we classified OV patients by their interferon-stimulated gene (ISG) expression profiles and investigated the associations between these subtypes, the immune microenvironment, and survival outcomes.MethodsWe employed consensus clustering in the TCGA-OV cohort (n = 376) to classify patients into ISG-related subgroups. Survival analysis, differential gene expression (DESeq), KEGG and GSEA pathway enrichment analyses, genomic variation assessments, immune cell profiling using the CIBERSORT algorithm, and TIDE analysis were conducted in the TCGA-OV cohort. In addition, immune checkpoint marker expressions were assessed using data from the TCGA-OV cohort and multiplex immunofluorescence (mIF) staining on an independent cohort (n = 80).ResultsTwo distinct ISG subtypes were identified: ISG Cluster A and ISG Cluster B. Patients in ISG Cluster B exhibited significantly improved overall survival (OS) (p = 0.0442). A total of 328 dysregulated genes were identified, with Cluster B showing overexpression of immune-related genes and enhanced involvement in immune signaling pathways. ISG Cluster B also presented higher tumor mutation burden (TMB) and an enriched immune profile, including M1 macrophages and CD8 + T cells. TIDE analysis indicated a more favorable response to immune checkpoint inhibitors in this cluster, corroborated by high expressions of PD-L1 and ISG15, which were associated with prolonged OS.ConclusionsOur findings demonstrate that ISG-related subtypes are significantly associated with the immune microenvironment and survival outcomes in OV. The biomarkers identified in this study have the potential to inform precision therapy development, thereby enhancing treatment efficacy and personalized care for OV patients.

Construction of a novel copper-induced-cell-death-related gene signature for prognosis in colon cancer, with focus on KIF7

BackgroundColon cancer (CC) is a leading cause of cancer-related mortality worldwide. Accurate prognostic markers are essential for patient risk stratification and personalized treatment. Copper-induced cell-death-related genes (CRG) have emerged as potential players in cancer prognosis, yet their role in CC remains unclear.MethodsThis study aimed to comprehensively evaluate the expression of CRG and their roles in CC using gene expression and clinical data from TCGA and GEO databases. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses identified prognostic genes, leading to the construction of a CRG prognostic signature. The signature’s predictive accuracy was validated using Kaplan-Meier survival curves, Receiver Operating Characteristic (ROC) curves, and a nomogram model. Additionally, we conducted experiments including immunofluorescence staining and cellular assays to validate the key genes’ biological functions.ResultsA 12-gene CRG signature was significantly associated with overall survival in CC patients. The high-risk group, as classified by median risk score, exhibited significantly shorter survival times compared to the low-risk group. The signature’s predictive accuracy was further confirmed with Area Under the Curve (AUC) scores exceeding 0.75 in TCGA and GSE17536 cohorts. Notably, the risk score was significantly correlated with immune checkpoints, chemotherapy sensitivity, and tumor microenvironment. Furthermore, the risk score showed a strong association with immunotherapy response in patients from GSE78220 and GSE39688 cohorts. Bioinformatics analysis of KIF7, a key gene within the signature, revealed its upregulation in CC and significant associations with tumor mutation burden, microsatellite instability, and immune cell infiltration across various cancers. Experiments confirmed that KIF7 was upregulated in CC and its knockdown reduced cell proliferation, migration, and invasion.ConclusionThe CRG prognostic signature can effectively predict overall survival, immune microenvironment and chemotherapy response in CC. KIF7, as a potential prognostic marker, has significant potential for the prediction and treatment of CC.

Diagnostic and Prognostic/Therapeutic Significance of Comprehensive Analysis of Bone and Soft Tissue Tumors Using Optical Genome Mapping and Next-generation Sequencing.

Detecting somatic structural variants (SVs), copy number variants (CNVs), and mutations in bone and soft tissue tumors is essential for accurately diagnosing, treating, and prognosticating outcomes. Optical genome mapping (OGM) holds promise to yield useful data on SVs and CNVs but requires fresh or snap-frozen tissue. This study aimed to evaluate the clinical utility of data from OGM compared to current standard-of-care cytogenetic testing. We evaluated 60 consecutive specimens from bone and soft tissue tumors using OGM and karyotyping, FISH, gene fusion assays, and deep next-generation sequencing (NGS). OGM accurately identified diagnostic SVs/CNVs previously detected by karyotyping and FISH (specificity=100%). OGM identified diagnostic and pathogenic SVs/CNVs (∼23% of cases) undetected by karyotyping (cryptic/submicroscopic). OGM allowed detection and further characterization of complex structural rearrangements including chromoanagenesis (27% of cases) and complex 3-6-way translocations (15% of cases). In addition to identifying 321 SVs and CNVs among cases with chromoanagenesis events, OGM identified approximately 9 SVs and 12 CNVs per sample. A combination of OGM and deep NGS data identified diagnostic and pathogenic SVs, CNVs, and mutations in ∼98% of cases. Our cohort contained the most extensive collection of bone and soft tissue tumors profiled by OGM. OGM had excellent concordance with standard-of-care cytogenetic testing, detecting and assigning high-resolution genome-wide genomic abnormalities with higher sensitivity than routine testing. This is the first and largest study to provide insights into the clinical utility of combined OGM and deep sequencing for the pathologic diagnosis and potential prognostication of bone and soft tissue tumors in routine clinical practice.

Preclinical Evaluation of [124I]-Sotorasib for the Imaging of Kirsten Rat Sarcoma G12C Mutant Tumors.

Kirsten rat sarcoma (KRAS) is a frequently mutated oncogene responsible for several oncogenic KRAS variants and for driving tumor proliferation. Some nonsmall cell lung cancer (NSCLC) tumors exhibit KRAS G12C mutations, which can be targeted for inhibition using covalent and more recently noncovalent inhibitors. Sotorasib was the first FDA-approved G12C inhibitor that has shown efficacy in lung cancer patients, but with mixed responses. The lack of efficacy can be attributed to tumor heterogeneity (lack of G12C mutations) and/or inefficient delivery. Targeted KRAS G12C imaging has potential to identify NSCLC lesions with the targeted mutation and elucidate the oncogene's role in driving tumor growth and correlating responses to treatment. Toward this goal, we have developed a sotorasib-based molecular agent for PET imaging and tested its efficacy in targeting tumor lesions with KRAS G12C mutations. Here, we describe the synthesis, in vitro and in vivo evaluation of an [124I]I-Sotorasib analog in targeting G12C mutant tumor lesions using PET imaging.

Advances in biomarkers for immunotherapy in small-cell lung cancer

Small-cell lung cancer (SCLC) is a refractory cancer with rapid growth and high aggressiveness. Extensive-stage SCLC is initially sensitive to chemotherapy; however, drug resistance and recurrence occur rapidly, resulting in a poor survival outcome due to lack of subsequently efficient therapy. The emergence of immune checkpoint inhibitors (ICIs) generated a new landscape of SCLC treatment and significantly prolonged the survival of patients. However, the unselected immunotherapy restrains both beneficiary population and responsive period in SCLC compared to the other tumors. The complex tumor origin, high heterogeneity, and immunosuppressive microenvironment may disturb the value of conventional biomarkers in SCLC including programmed cell death 1 ligand 1 and tumor mutation burden. Transcriptional regulator–based subtypes of SCLC are current research hotspot, revealing that Y (I) subtype can benefit from ICIs. Additionally, molecules related to immune microenvironment, immunogenicity, epigenetics, and SCLC itself also indicated the therapeutic benefits of ICIs, becoming potential predictive biomarkers. In this review, we discussed the advances of biomarkers for prediction and prognosis of immunotherapy, promising directions in the future, and provide reference and options for precision immunotherapy and survival improvement in patients with SCLC.

The role of silent mutations in KRAS-mutant tumors.

Silent mutations within the RASgene have garnered increasing attention for their potential roles in tumorigenesis and therapeutic strategies. Kirsten-RAS (KRAS)mutations, predominantly oncogenic, are pivotal drivers in various cancers. While extensive research has elucidated the molecular mechanisms and biological consequences of active KRASmutations, the functional significance of silent mutations remains relatively understudied. This review synthesizes current knowledge on KRASsilent mutations, highlighting their impact on cancer development. Silent mutations, which do not alter protein sequences but can affect RNA stability and translational efficiency, pose intriguing questions regarding their contribution to tumor biology. Understanding these mutations is crucial for comprehensively unraveling KRAS-driven oncogenesis and exploring novel therapeutic avenues. Moreover, investigations into the clinical implications of silent mutations in KRAS-mutant tumors suggest potential diagnostic and therapeutic strategies. Despite being in early stages, research on KRASsilent mutations holds promise for uncovering novel insights that could inform personalized cancer treatments. In conclusion, this review underscores the evolving landscape of KRASsilent mutations, advocating for further exploration to bridge fundamental biology with clinical applications in oncology.

Research progress on pathogenic germline mutations in malignant tumors

Malignant tumors are closely related to various genetic and environmental factors. Pathogenic germline gene mutations play a key role in the occurrence and development of some malignant tumors. Some germline mutations can increase the risk of malignant tumors. For example, those with homologous recombination repair gene BRCA1/2 mutations are prone to breast cancer, ovarian cancer, etc., and some germline mutations are associated with genetic syndromes. For instance, 80% of hereditary non-polyposis colon cancers are associated with mutations in mismatch repair genes such as MLH1 and MLH2. In addition, 70% of Li-Fraumeni syndrome patients have harbored germline TP53 mutations. With the development of next-generation sequencing technology, more and more germline gene mutations have been discovered recently, which is of great significance for the prevention, screening, and treatment of tumors. This article has provided a review for common germline mutations, detection methods, and advances in drug therapy.

The roles of G protein-coupled receptor genes and the tumor microenvironment in esophageal squamous cell carcinoma

Abstract Objectives Esophageal squamous cell carcinoma (ESCA) is a challenging disease characterized by a high mortality rate. Understanding the prognostic relationship between G protein-coupled receptors (GPR) and ESCA is critical for improving patient outcomes, yet this connection remains to be fully explored. Methods In this study, we examined the roles of GPR genes and the tumor microenvironment (TME) in ESCA development and progression. Cox regression and Kaplan–Meier analysis demonstrated the predictive value of these genes. Our analysis of TME cell-cell communication revealed extensive interactions, particularly involving neutrophils. We also assessed the combined predictive value of GPR genes, TME score, and tumor mutation burden (TMB) for patient prognosis in ESCA, ultimately constructing a GPR-TME-TMB classifier for prognosis prediction. Results We identified significant differences in GPR gene expression between normal and tumor tissues, with four genes (GPER1, GPR82, FFAR2, and HCAR3) correlating with patient prognosis. Single-cell RNA sequencing analysis revealed 10 major cell types in the TME, with GPR gene expression highly enriched in neutrophils. Our findings indicate that the GPR-TME-TMB classifier is strongly associated with patient prognoses. Additionally, our results align with previous studies on the roles of GPR genes and the TME in ESCA. Conclusions Our results suggest that GPR-related genes play a role in ESCA progression and are strongly associated with TME in ESCA. We constructed a GPR-TME classifier for ESCA to provide new directions for the treatment and prognosis of ESCA patients.

Abstract IA020: Discovery of brain-penetrant inhibitors for the treatment of BRAF mutant tumors

Abstract Many tumors are driven by oncogenic kinases. While a majority of the most prevalent oncogenic kinases currently have existing targeted therapies available, most of the molecules were not designed to be CNS penetrant and are therefore unable to control CNS metastatic tumors. By employing principles for the design of CNS penetrant molecules, we discovered two brain-penetrant BRAF inhibitors, which both progressed into clinical trials. The first candidate, ARRY-461, was designed to inhibit class I mutant BRAF V600E tumors. The second candidate, ARRY-440, was designed to inhibit class I, II, III, and indel mutant BRAF tumors. Additionally, ARRY-440 was designed to overcome both the paradoxical activation of BRAF as well as inhibit mBRAF:wtCRAF heterodimers, two features that most 1st generation BRAF V600E inhibitors lack. Finally, we were pleased to see that ARRY-440 led to clinical responses in a variety of different BRAF V600E tumors, including in some tumors that harbored both a BRAF V600E mutation and an oncogenic NRAS mutation. Citation Format: Dean Kahn. Discovery of brain-penetrant inhibitors for the treatment of BRAF mutant tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr IA020.

Direct comparison of an ultrasensitive real-time PCR assay with droplet digital PCR for the detection of PIK3CA hotspot mutations in primary tumors, plasma cell-free DNA and paired CTC-derived gDNAs

IntroductionDetection of PIK3CA mutations in primary tumors and liquid biopsy samples is of increasing importance for treatment decisions and therapy resistance in many types of cancer. The aim of the present study was to directly compare the efficacy of a relatively inexpensive ultrasensitive real-time PCR with the well-established and highly sensitive technology of ddPCR for the detection of the three most common hotspot mutations of PIK3CA, in exons 9 and 20, that are all of clinical importance in various types of cancer.Patients and methodsWe analyzed 42 gDNAs from primary tumors (FFPEs), 29 plasma-cfDNA samples, and 29 paired CTC-derived gDNAs, all from patients with ER+ metastatic breast cancer, and plasma from 10 healthy donors. The same blood draws were used for CTC isolation using EpCAM beads for positive immunomagnetic enrichment. All FFPEs and plasma-cfDNA samples were analyzed in parallel for PIK3CA mutations by ultrasensitive real-time PCR assay and droplet digital PCR.ResultsIn gDNAs from FFPEs, using ultrasensitive real-time PCR, the p.E545K mutation was detected in 22/42(52.4%), and the p.E542K and p.H1047R mutations were detected in 14/42(33.3%) and 16/42(38.1%), respectively. Using ddPCR, the p.E545K mutation was detected in 22/42(52.4%), p.E542K in 17/42(40.5%), and p.H1047R in 19/42(45.2%) samples, revealing a concordance between the two methodologies of 81%, 78.6% and 78.6% for each mutation respectively. In plasma-cfDNA, using ultrasensitive real-time PCR, the p.E545K mutation was detected in 11/29(38%) and both p.E542K and p.H1047R mutations in 2/29(6.9%).In the same plasma-cfDNA samples using ddPCR, p.E545K was detected in 1/29(3.5%), p.E542K in 2/29(6.9%), and p.H1047R in 3/29(10.5%) samples, revealing a concordance of 65.5%,100% and 93.1% for each mutation respectively. In paired CTC-derived gDNAs p.E545K was detected in 11/29(38%), p.E542K in 3/29(10.3%), and p.H1047R in 7/29(24.1%) samples.ConclusionsThis low-cost, high-throughput and ultrasensitive real-time PCR assay provides accurate and specific detection of PIK3CA hotspot mutations in liquid biopsy samples and gives similar results to ddPCR. This assay can be performed in labs where digital PCR instrumentation is not available. In CTC-derived gDNA and paired plasma-cfDNA, PIK3CA mutations detected were not identical, revealing that CTC and plasma-cfDNA give complementary information.

Integrative analysis of a novel immunogenic PANoptosis‑related gene signature in diffuse large B-cell lymphoma for prognostication and therapeutic decision-making

This study aimed to develop a PANoptosis-related gene prognostic index (PANGPI) to explore its potential value in predicting the prognosis and immunotherapy response of diffuse large B-cell lymphoma (DLBCL). Differentially expressed genes of DLBCL from GEO databases were analyzed and mapped to the PANoptosis gene set. The independent prognostic value of the PANGPI signature was evaluated using LASSO Cox regression and multivariate Cox regression. Additionally, the tumor infiltrating lymphocyte (TIL) characteristics and mutation landscape of both subgroups were evaluated, and drug sensitivity was predicted using the GDSC database. Furthermore, in silico docking and molecular dynamic simulation studies were presented to elucidate the mode of interaction of these predicted drugs. The PANGPI risk score was an independent risk factor for the prognosis of patients with DLBCL and exhibited good prognostic predictive performance. Furthermore, the cytolytic activity of the TILs was positively correlated with the PANGPI scores. Additionally, the PANGPI enabled the identification of 3 chemotherapeutic agents, including BMS-536924, Gefitinib, Navitoclax for DLBCL patients in the high-risk group. We established a novel PANoptosis-related gene subtyping system in DLBCL, which could shed a novel light on the development of new biomarkers for DLBCL.

Epidermal Growth Factor Receptor (EGFR) and SMAD4 negatively correlated in the progression of gallbladder cancer in Eastern Indian patients

Background and introductionTwo and half percent of the Indian population suffer from gallbladder cancer (GBC). The primary factors that lead GBC are associated with mutation of several protooncogenes such as EGFR, ERBB2, Myc, and CCND1 along with dysregulation of several tumor suppressor genes such as SMAD4 and CDKN2A. Bacterial infection caused by S.typhi and H.pylori are also hypothesized to be potential factors driving GBC.AimsThis study aims to investigate the molecular mechanisms driving the progression of gallbladder adenocarcinoma in Eastern Indian patients. We specifically focussed on analyzing the mutational status of the KRAS gene, examining the amplification of the ERBB2/Her2-neu gene, and evaluating the expression patterns of six dysregulated genes (CCND1, MYC, EGFR, ERBB2/Her2-neu, CDKN2A, SMAD4). Additionally, we assessed the expression status of TGF-beta, the association between bacterial infections (S. Typhi and H. pylori) and GBC, and the impact of single nucleotide polymorphisms in ERBB2/Her2-neu and CCND1 genes within this population.MethodsSixty-seven samples from GBC-diagnosed patients, 26 other unrelated GBC samples for validation cohort, and 68 gallstone tissue samples were collected for this study. Genomic DNA from normal as well as tumor tissues were isolated, exon 2 and exon 3 of KRAS gene were amplified along, DNA sequenced and analyzed. KRAS codon 12 mutation was detected by allele specific PCR (ASPCR) method. Amplification of UreC A (coding for urease subunit α), VacA (coding for Vacuolating cytotoxin A) and CagA genes (coding for cytotoxin-associated gene A) in H.pylori were amplified using PCR. Similarly, FlicC (coding for flagellin gene C) in S.typhi was amplified using PCR. The ERBB2/Her2-neu SNP I655V, and CCND1 SNP A870G were analyzed using PCR followed by RFLP. Expression studies of CCND1, Myc, CDKN2A, ERBB2/Her2-neu, EGFR, and SMAD4 genes were measured in GBC tumor tissues by sybr green quantitative RT PCR.ResultsThe oncogenes (EGFR and ERBB2/Her2-neu) were statistically significantly overexpressed and the tumor suppressor gene (SMAD4) downregulated in our GBC tumor patient samples. The EGFR and SMAD4 genes were negatively correlated (r = -0.01) in GBC patients and the data is statistically significant and validated through IHC technique. A significant downregulation of TGF-beta had also been observed. Lower frequency (i.e. 11.5%) of KRAS mutation in GBC tumor was observed.ConclusionsEGFR and SMAD4 expression were found to be negatively correlated in GBC tissue samples. ERBB2 overexpression/amplification was observed in 30% of the GBC samples. We also found a low percentage of GBC samples to show KRAS codon 12 mutation in Indian GBC patient population, as had been previously documented in pancreatic cancers.

Blood-based tumor mutational burden impacts clinical outcomes of immune checkpoint inhibitor treated breast and prostate cancers

BackgroundBreast and prostate tumors are known to be less responsive to immune checkpoint inhibitors (ICIs). Tissue-based tumor mutation burden (tTMB) has emerged as a predictive biomarker of response to ICIs, including in these “cold tumors”. In clinical practice, when tTMB is not available, blood-based TMB score (bTMB) can be used to consider treatment with ICIs.MethodsThis retrospective, real-world study included a final cohort of metastatic breast and prostate cancer patients treated with an ICI following a liquid biopsy test. Multiple bTMB-High cut-offs were assessed. Clinical, genomic, and outcomes data were collected. We hypothesized that a cut-off of bTMB ≥10 mut/Mb is not a strong predictor of response to ICIs in this setting. The Guardant Health genomic database (GHGD) was then queried (N = 13,992) for associations of bTMB with genomic alterations.ResultsIn the clinical cohort (N = 48), ICI treatment is offered after a median of 3 (1–9) lines of treatment. The median bTMB is 16.4 (10–186) mut/Mb. The median time on ICI and PFS is 2.1 (0–1.7) and 3.1 months (95%CI, 1.6–4.6) respectively; no difference by MSI/MMR status (p = 0.152). Response rate among eligible patients (n = 36) is 16.7%; only N = 1/6 in bTMB <16 mut/Mb. High bMSI is associated with higher bTMB (correlation test, r = 0.66, p = 0.000). In the GHGD, patients with bTMB high have significantly more alterations than bTMB low and TP53, PIK3CA, ATM, ESR1, NF1, BRCA2, ARID1A, and APC were the most frequently altered genes.ConclusionsIn this study, the practice of offering an ICIs based on bTMB was uncommon and did not independently predict ICI benefits in patients with refractory, advanced breast and prostate cancers.

Real-World Prevalence, Treatment Patterns, and Outcomes for Patients With HER2 (ERBB2)-Mutant Metastatic Non-Small Cell Lung Cancer, From a US-Based Clinico-Genomic Database.

Targeted therapies have been shown to improve outcomes in metastatic non-small cell lung cancer (mNSCLC) with driver mutations. We evaluated the real-world prevalence of human epidermal growth factor receptor 2 (HER2; ERBB2) tumor gene mutations among patients with mNSCLC and described historical treatments and outcomes in patients with HER2-mutant mNSCLC, during a period when there was no approved targeted therapy for HER2-mutant mNSCLC. This retrospective observational study used a US nationwide de-identified NSCLC clinico-genomic database. Eligible patients were adults diagnosed with HER2-mutant mNSCLC from January 2014 to July 2021 without co-occuring epidermal growth factor receptor (EGFR) tumor mutations. Descriptive statistics were used to summarize prevalence, baseline characteristics and treatment patterns. Clinical outcomes were estimated with Kaplan-Meier analyses. Among 9206 patients with mNSCLC, 164 (1.78%) met the eligibility criteria (mean age: 67.3 years, 63.4% White, 56.7% female, and 53.0% with a smoking history). 132/164 (80.5%) had at least one line of treatment. Platinum-based chemotherapy (45.5%) and immune checkpoint inhibitor (ICI) with chemotherapy (28.0%) were the most frequently used first-line treatments. The median (95% confidence interval [CI]) real-world (rw) progression-free survival in first-line was 5.5 (4.8, 6.2) months and 3.0 (2.3, 4.2) months in second-line. The median rw overall survival in first-line was 13.2 (10.6, 18.4) months and 8.2 (6.6, 13.2) months in second-line. During this study period, the most common regimens were platinum-based chemotherapy with or without ICI in first and second line, and median rwOS was 13.2 and 8.2 months, respectively. These results indicate the need for more effective targeted therapies in this patient population.

Effective treatment strategies and key factors influencing therapeutic efficacy in advanced SMARCA4-deficient non-small cell lung cancer

IntroductionSMARCA4/BRG1-deficient non-small cell lung cancer (SD-NSCLC) with high invasiveness and poor prognosis is associated with primary resistance to standard treatment, especially in late-stage patients. This study aimed to explore effective treatments and identify critical factors impacting therapeutic efficacy to enhance outcomes for SD-NSCLC patients. Methods103 SD-NSCLC patients in stage III/IV diagnosed by immunohistochemistry from May 2019 to March 2024 were included in this study. We assessed the patients’ clinical and genetic features, analyzed the clinical outcomes of local treatment and immunotherapy according to the TNM stage, and further evaluated the factors impacting therapeutic efficacy. ResultsIn stage III patients, no significant differences in the median progression-free survival (mPFS) and median overall survival (mOS) were observed between patients receiving local treatment at the primary site and those who did not (p > 0.05), while adding ICIs (immune checkpoint inhibitors) to local treatment significantly improved mPFS compared with non-ICIs (15.0 vs. 7.7 months, p = 0.033), though not mOS (p > 0.05). For stage IV patients, ICIs significantly improved mPFS (8.9 vs. 4.2 months, p = 0.006) and mOS (19.7 vs. 13.1 months, p = 0.007) compared to non-ICIs treatments. However, among ICIs-treated patients, the addition of local treatment to the primary lesion did not significantly affect mPFS and mOS (p > 0.05). Patients with STK11/KEAP1 mutations had significantly shorter mPFS (3.6 vs. 16.2 months, p = 0.001) and mOS (17.7 vs. 31.3 months, p = 0.002), while no significant difference was observed in mPFS and mOS in patients with different tumor mutation burden (TMB) and PD-L1 expression levels. ConclusionICIs to local treatment shows promising results for locally advanced patients with SD-NSCLC, and first-line ICIs are associated with improved survival in metastatic SD-NSCLC. STK11/KEAP1 mutations may be linked to reduced efficacy of immunotherapy.

Lung adenocarcinomas with mucinous histology: clinical, genomic, and immune microenvironment characterization and outcomes to immunotherapy-based treatments and KRASG12C inhibitors

BackgroundApproximately 10% of lung adenocarcinomas (LUAD) have mucinous histology (LUADMuc), which is associated to a light/absent smoking history and a high prevalence of KRAS mutations. We sought to characterize LUADMuc by comparing it to LUAD without mucinous histology (LUADnon-muc) and determine the relative benefit of current treatments. Patients and MethodsPatients with LUAD from five institutions and TCGA PanCancer Atlas classified as LUADMuc or LUADnon-muc were included. Clinicopathologic, genomic, immunophenotypic, transcriptional features, and treatment outcomes were compared between LUADMuc and LUADnon-muc. ResultsOf 4,082 patients with LUAD, 9.9% had LUADMuc. Compared to LUADnon-muc, patients with LUADMuc had a lighter smoking history (median: 15 vs 20 pack-years, P=0.008), lower PD-L1 TPS (median: 0% vs 5%, P<0.0001), and lower tumor mutation burden (median: 6.8 vs 8.5 mutations/megabase, P<0.0001). Mutations in KRAS, NKX2-1 (TTF-1), STK11, SMARCA4, GNAS, and ALK rearrangements were enriched in LUADMuc, while TP53, EGFR, BRAF, and MET mutations were enriched in LUADnon-muc. At stage IV diagnosis, LUADMuc was more likely to have contralateral lung metastasis (55.2% vs 36.9%, P<0.0001) and less likely to have brain metastases (23.3% vs 41.9%, P<0.0001). Compared to LUADnon-muc, LUADMuc cases showed lower intratumor CD8+, PD-1+, CD8+PD-1+, and FOXP3+ cells. Among metastatic cases receiving ICIs, compared to LUADnon-muc (N=1,511), LUADMuc (N=112) had lower objective response rate (ORR, 8.4% vs 25.9%, P<0.0001), and shorter median progression-free survival (mPFS, 2.6 vs 3.9 months, P<0.0001) and overall survival (mOS, 9.9 vs 17.2 months, P<0.0001). Similarly, patients with LUADMuc had worse outcomes to chemo-immunotherapy. LUADMuc (N=18) and LUADnon-muc (N=150) had similar ORR (16.7% vs 34.9%, P=0.12) and mPFS (4.6 vs 5.6 months, P=0.17) to treatment with KRASG12C inhibitors, but LUADMuc had shorter mOS (6.8 vs 10.8 months, P=0.018). ConclusionLUADMuc represents a distinct LUAD subpopulation with unique clinicopathologic, genomic, immunophenotypic, and transcriptional features, achieving worse outcomes to standard immunotherapy-based treatments.