Resistance to Combined Anthracycline-Taxane Chemotherapy Is Associated with Altered Metabolism and Inflammation in Breast Carcinomas.

Approximately 30% of early-stage breast cancer (BC) patients experience recurrence after systemic chemotherapy; thus, understanding therapy resistance is crucial in developing more successful treatments. Here, we investigated the mechanisms underlying resistance to combined anthracycline-taxane treatment by comparing gene expression patterns with subsequent therapeutic responses. We established a cohort of 634 anthracycline-taxane-treated patients with pathological complete response (PCR) and a separate cohort of 187 patients with relapse-free survival (RFS) data, each having transcriptome-level expression data of 10,017 unique genes. Patients were categorized as responders and non-responders based on their PCR and RFS status, and the expression for each gene was compared between the two groups using a Mann-Whitney U-test. Statistical significance was set at p < 0.05, with fold change (FC) > 1.44. Altogether, 224 overexpressed genes were identified in the tumor samples derived from the patients without PCR; among these, the gene sets associated with xenobiotic metabolism (e.g., CYP3A4, CYP2A6) exhibited significant enrichment. The genes ORAI3 and BCAM differentiated non-responders from responders with the highest AUC values (AUC > 0.75, p < 0.0001). We identified 51 upregulated genes in the tumor samples derived from the patients with relapse within 60 months, participating primarily in inflammation and innate immune responses (e.g., LYN, LY96, ANXA1). Furthermore, the amino acid transporter SLC7A5, distinguishing non-responders from responders, had significantly higher expression in tumors and metastases than in normal tissues (Kruskal-Wallis p = 8.2 × 10-20). The identified biomarkers underscore the significance of tumor metabolism and microenvironment in treatment resistance and can serve as a foundation for preclinical validation studies.

Dietary approaches for exploiting metabolic vulnerabilities in cancer.

Renewed interest in tumor metabolism sparked an enthusiasm for dietary interventions to prevent and treat cancer. Changes in diet impact circulating nutrient levels in the plasma and the tumor microenvironment, and preclinical studies suggest that dietary approaches, including caloric and nutrient restrictions, can modulate tumor initiation, progression, and metastasis. Cancers are heterogeneous in their metabolic dependencies and preferred energy sources and can be addicted to glucose, fructose, amino acids, or lipids for survival and growth. This dependence is influenced by tumor type, anatomical location, tissue of origin, aberrant signaling, and the microenvironment. This review summarizes nutrient dependencies and the related signaling pathway activations that provide targets for nutritional interventions. We examine popular dietary approaches used as adjuvants to anticancer therapies, encompassing caloric restrictions, including time-restricted feeding, intermittent fasting, fasting-mimicking diets (FMDs), and nutrient restrictions, notably the ketogenic diet. Despite promising results, much of the knowledge on dietary restrictions comes from in vitro and animal studies, which may not accurately reflect real-life situations. Further research is needed to determine the optimal duration, timing, safety, and efficacy of dietary restrictions for different cancers and treatments. In addition, well-designed human trials are necessary to establish the link between specific metabolic vulnerabilities and targeted dietary interventions. However, low patient compliance in clinical trials remains a significant challenge.

[Increased activity of inflammation-related signaling pathways in anthracycline- paclitaxel resistant breast carcinomas]. / A gyulladáshoz kötheto jelátviteli utak fokozott aktivitása antraciklin-paklitaxel rezisztens emlokarcinómákban.

A frequently recommended systemic therapy for breast cancer involves a combination of anthracyclines and taxanes, however, approximately 30% of patients experience recurrence. We aimed to investigate the mechanisms of resistance to anthracycline-paclitaxel based treatment by analyzing gene expression patterns in tumor samples collected during surgery and subsequent therapeutic responses. A database of 187 patients with information about relapse-free survival (RFS) allowed the analysis of 10,017 genes. Patients were divided into responders and nonresponders based on whether relapse occurred within sixty months. The expression of each gene was compared between the two groups using the Mann-Whitney U-test, with a statistical significance set at p <0.05 and fold change (FC) ≥1.44. We identified 51 up-regulated genes among nonresponders, primarily associated with inflammatory processes and the innate immune response. The high expression of SLC7A5, encoding an amino acid transporter, was linked to worse overall survival (p = 2.3E-10), with elevated expression in tumors (p = 2.94E-20), and further increase in metastases (p = 1.33E-10). Our results emphasize the significance of tumor microenvironment and metabolism in therapy resistance. These findings may allow better patient classification and identification of relevant treatment targets.

[Diagnosis of genetic disorders in childhood with next-generation sequencing]. / Gyermekkori genetikai rendellenességek diagnosztikája újgenerációs szekvenálással.

Incorporating next-generation sequencing (NGS) technology to diagnostics enables to identify a vast repertoire of genetic disorders in a single measurement. Currently, targeted gene panels and whole-exome sequencing (WES) are the most prevalent methods in clinical use due to the smaller cost of analysis and manageable amount of data compared to whole-genome sequencing (WGS). We aim to review the applicability of NGS-based technologies in the diagnosis of early-onset genetic disorders. We summarize genes associated with early-onset diseases including inborn errors of metabolism, oncological indications and pediatric genetic disorders. There are several technical and clinical issues that currently limit the everyday diagnostic application of NGS. The principal challenge lies in the interpretation of rare genetic variants and in the correct assignment of variant pathogenicity. Orv Hetil. 2022; 163(51): 2027-2040.

Correction: MultipleTesting.com: A tool for life science researchers for multiple hypothesis testing correction.

[This corrects the article DOI: 10.1371/journal.pone.0245824.].

MultipleTesting.com: A tool for life science researchers for multiple hypothesis testing correction.

Scientists from nearly all disciplines face the problem of simultaneously evaluating many hypotheses. Conducting multiple comparisons increases the likelihood that a non-negligible proportion of associations will be false positives, clouding real discoveries. Drawing valid conclusions require taking into account the number of performed statistical tests and adjusting the statistical confidence measures. Several strategies exist to overcome the problem of multiple hypothesis testing. We aim to summarize critical statistical concepts and widely used correction approaches while also draw attention to frequently misinterpreted notions of statistical inference. We provide a step-by-step description of each multiple-testing correction method with clear examples and present an easy-to-follow guide for selecting the most suitable correction technique. To facilitate multiple-testing corrections, we developed a fully automated solution not requiring programming skills or the use of a command line. Our registration free online tool is available at www.multipletesting.com and compiles the five most frequently used adjustment tools, including the Bonferroni, the Holm (step-down), the Hochberg (step-up) corrections, allows to calculate False Discovery Rates (FDR) and q-values. The current summary provides a much needed practical synthesis of basic statistical concepts regarding multiple hypothesis testing in a comprehensible language with well-illustrated examples. The web tool will fill the gap for life science researchers by providing a user-friendly substitute for command-line alternatives.

Gene expression-based biomarkers designating glioblastomas resistant to multiple treatment strategies.

Despite advances in molecular characterization of glioblastoma multiforme (GBM), only a handful of predictive biomarkers exist with limited clinical relevance. We aimed to identify differentially expressed genes in tumor samples collected at surgery associated with response to subsequent treatment, including temozolomide (TMZ) and nitrosoureas. Gene expression was collected from multiple independent datasets. Patients were categorized as responders/nonresponders based on their survival status at 16 months postsurgery. For each gene, the expression was compared between responders and nonresponders with a Mann-Whitney U-test and receiver operating characteristic. The package 'roc' was used to calculate the area under the curve (AUC). The integrated database comprises 454 GBM patients from 3 independent datasets and 10 103 genes. The highest proportion of responders (68%) were among patients treated with TMZ combined with nitrosoureas, where FCGR2B upregulation provided the strongest predictive value (AUC = 0.72, P < 0.001). Elevated expression of CSTA and MRPS17 was associated with a lack of response to multiple treatment strategies. DLL3 upregulation was present in subsequent responders to any treatment combination containing TMZ. Three genes (PLSCR1, MX1 and MDM2) upregulated both in the younger cohort and in patients expressing low MGMT delineate a subset of patients with worse prognosis within a population generally associated with a favorable outcome. The identified transcriptomic changes provide biomarkers of responsiveness, offer avenues for preclinical studies and may enhance future GBM patient stratifications. The described methodology provides a reliable pipeline for the initial testing of potential biomarker candidates for future validation studies.

Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis.

While cost-effective high-throughput technologies provide an increasing amount of data, the analyses of single layers of data seldom provide causal relations. Multi-omics data integration strategies across different cellular function levels, including genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes offer unparalleled opportunities to understand the underlying biology of complex diseases, such as cancer. We review some of the most frequently used data integration methods and outline research areas where multi-omics significantly benefit our understanding of the process and outcome of the malignant transformation. We discuss algorithmic frameworks developed to reveal cancer subtypes, disease mechanisms, and methods for identifying driver genomic alterations and consider the significance of multi-omics in tumor classifications, diagnostics, and prognostications. We provide a comprehensive summary of each omics strategy's most recent advances within the clinical context and discuss the main challenges facing their clinical implementations. Despite its unparalleled advantages, multi-omics data integration is slow to enter everyday clinics. One major obstacle is the uneven maturity of different omics approaches and the growing gap between generating large volumes of data compared to data processing capacity. Progressive initiatives to enforce the standardization of sample processing and analytical pipelines, multidisciplinary training of experts for data analysis and interpretation are vital to facilitate the translatability of theoretical findings.

Molecular stratifications, biomarker candidates and new therapeutic options in current medulloblastoma treatment approaches.

Medulloblastoma (MB) is the most common malignant childhood tumor of the brain. Multimodal treatment consisting of surgery, radiation therapy, and chemotherapy reduced cumulative incidence of late mortality but increased the incidence of subsequent neoplasms and severe, incapacitating chronic health conditions. Present treatment strategies fail to recognize heterogeneity within patients despite wide divergence in individual responses. The persistent mortality rates and serious side effects of non-targeted cytotoxic therapies indicate a need for more refined therapeutic approaches. Advanced genomic research has led to the accumulation of an enormous amount of genetic information and resulted in a consensus distinguishing four molecular subgroups, WNT-activated, SHH-activated, and Group 3 and 4 medulloblastomas. These have distinct origin, demographics, molecular alterations, and clinical outcomes. Although subgroup affiliation does not predict response to therapy, new subgroup-specific markers of prognosis can enable a more layered risk stratification with additional subtypes within each primary subgroup. Here, we summarize subgroup-specific genetic alterations and their utility in current treatment strategies. The transition toward molecularly targeted interventions for newly diagnosed MBs remains slow, and prospective trials are needed to confirm stratifications based on molecular alterations. At the same time, numerous studies focus at fine-tuning the intensity of invasive radio- and chemotherapies to reduce intervention-related long-term morbidity. There are an increasing number of immunotherapy-based treatment strategies including immune checkpoint-inhibitors, oncolytic viruses, CAR-T therapy, and NK cells in recurrent and refractory MBs. Although most trials are in early phase, there is hope for therapeutic breakthroughs for advanced MBs within the next decade.

[Subgroup-specific genomic alterations and potential prognostic biomarkers in childhood medulloblastomas]. / Alcsoport-specifikus genomi eltérések és lehetséges prognosztikus markerek gyermekkori medulloblasztómában.

Despite continuing advances in therapeutic strategies, survival of childhood medulloblastoma (MB) patients has reached a plateau in the past decade. Current clinical approaches divide patients into average- and high-risk treatment categories, although this categorization does not take patient heterogeneity into account. Advanced genomics has initiated an exciting transition that lead to a consensus of four distinct molecular entities within MBs (WNT-activated, SHH-activated, Group 3 MB, and Group 4 MB), each with distinct origins, demographics, molecular alterations and clinical outcomes. Within each of the four primary subgroups additional subtypes started to emerge with distinct biological backgrounds and clinical outcomes. Here we summarize subgroup-specific genomic alterations, affected signaling pathways and potential prognostic biomarkers. The poor prognosis associated with recurrent disease is responsible for the stagnant survival rates. Nevertheless, the mortality is unlikely to change without new biomarkers linked to different mechanisms of pathway activation.

The prognostic association of SPAG5 gene expression in breast cancer patients with systematic therapy.

BACKGROUND: Despite much effort on the treatment of breast cancer over the decades, a great uncertainty regarding the appropriate molecular biomarkers and optimal therapeutic strategy still exists. This research was performed to analyze the association of SPAG5 gene expression with clinicopathological factors and survival outcomes. METHODS: We used a breast cancer database including 5667 patients with a mean follow-up of 69 months. Kaplan-Meier survival analyses for relapse free survival (RFS), overall survival (OS), and distant metastasis-free survival (DMFS) were performed. In addition, ROC analysis was performed to validate SPAG5 as a prognostic candidate gene. RESULTS: Mean SPAG5 expression value was significantly higher with some clinicopathological factors that resulted in tumor promotion and progression, including poor differentiated type, HER2 positive or TP53 mutated breast cancer. Based on ROC-analysis SPAG 5 is a suitable prognostic marker of poor survival. In patients who received chemotherapy alone, SPAG5 had only a moderate and not significant predictive impact on survival outcomes. However, in hormonal therapy, high SPAG5 expression could strongly predict prognosis with detrimental RFS (HR = 1.57, 95% CI 1.2-2.06, p = 0.001), OS (HR = 2, 95% CI 1.05-3.8, p = 0.03) and DMFS (HR = 2.36, 95% CI 1.57-3.54, p <  0.001), respectively. In addition, SPAG5 could only serve as a survival predictor in ER+, but not ER- breast cancer patients. Patients might also be at an increased risk of relapse despite being diagnosed with a lower grade cancer (well differentiated type). CONCLUSIONS: SPAG5 could be used as an independent prognostic and predictive biomarker that might have clinical utility, especially in ER+ breast cancer patients who received hormonal therapy.

Uncovering Potential Therapeutic Targets in Colorectal Cancer by Deciphering Mutational Status and Expression of Druggable Oncogenes.

BACKGROUND: Numerous driver mutations have been identified in colorectal cancer (CRC), but their relevance to the development of targeted therapies remains elusive. The secondary effects of pathogenic driver mutations on downstream signaling pathways offer a potential approach for the identification of therapeutic targets. We aimed to identify differentially expressed genes as potential drug targets linked to driver mutations. METHODS: Somatic mutations and the gene expression data of 582 CRC patients were utilized, incorporating the mutational status of 39,916 and the expression levels of 20,500 genes. To uncover candidate targets, the expression levels of various genes in wild-type and mutant cases for the most frequent disruptive mutations were compared with a Mann-Whitney test. A survival analysis was performed in 2100 patients with transcriptomic gene expression data. Up-regulated genes associated with worse survival were filtered for potentially actionable targets. The most significant hits were validated in an independent set of 171 CRC patients. RESULTS: Altogether, 426 disruptive mutation-associated upregulated genes were identified. Among these, 95 were linked to worse recurrence-free survival (RFS). Based on the druggability filter, 37 potentially actionable targets were revealed. We selected seven genes and validated their expression in 171 patient specimens. The best independently validated combinations were DUSP4 (p = 2.6 × 10-12) in ACVR2A mutated (7.7%) patients; BMP4 (p = 1.6 × 10-04) in SOX9 mutated (8.1%) patients; TRIB2 (p = 1.35 × 10-14) in ACVR2A mutated patients; VSIG4 (p = 2.6 × 10-05) in ANK3 mutated (7.6%) patients, and DUSP4 (p = 7.1 × 10-04) in AMER1 mutated (8.2%) patients. CONCLUSIONS: The results uncovered potentially druggable genes in colorectal cancer. The identified mutations could enable future patient stratification for targeted therapy.

Gene Expression Indicates Altered Immune Modulation and Signaling Pathway Activation in Ovarian Cancer Patients Resistant to Topotecan.

Epithelial ovarian cancer (EOC) is one of the deadliest gynecological malignancies. Topotecan remains an essential tool in second-line therapy; even so, most patients develop resistance within a short period of time. We aimed to identify biomarkers of topotecan resistance by using gene expression signatures derived from patient specimens at surgery and available subsequent responses to therapy. Gene expression was collected for 1436 patients and 10,103 genes. Based on disease progression, patients were categorized as responders/nonresponders depending on their progression free survival (PFS) state at 9, 12, 15 and 18 months after surgery. For each gene, the median expression was compared between responders and nonresponders for two treatment regimens (chemotherapy including/excluding topotecan) with Mann-Whitney U test at each of the four different PFS cutoffs. Statistical significance was accepted in the case of p < 0.05 with a fold change (FC) ≥ 1.44. Four genes (EPB41L2, HLA-DQB1, LTF and SFRP1) were consistently overexpressed across multiple PFS cutoff times in initial tumor samples of patients with disease progression following topotecan treatment. A common theme linked to topotecan resistance was altered immune modulation. Genes associated with disease progression after systemic chemotherapy emphasize the role of the initial organization of the tumor microenvironment in therapy resistance. Our results uncover biomarkers with potential utility for patient stratification.

Principles of tumorigenesis and emerging molecular drivers of SHH-activated medulloblastomas.

SHH-activated medulloblastomas (SHH-MB) account for 25-30% of all medulloblastomas (MB) and occur with a bimodal age distribution, encompassing many infant and adult, but fewer childhood cases. Different age groups are characterized by distinct survival outcomes and age-specific alterations of regulatory pathways. Here, we review SHH-specific genetic aberrations and signaling pathways. Over 95% of SHH-MBs contain at least one driver event - the activating mutations frequently affect sonic hedgehog signaling (PTCH1, SMO, SUFU), genome maintenance (TP53), and chromatin modulation (KMT2D, KMT2C, HAT complexes), while genes responsible for transcriptional regulation (MYCN) are recurrently amplified. SHH-MBs have the highest prevalence of damaging germline mutations among all MBs. TP53-mutant MBs are enriched among older children and have the worst prognosis among all SHH-MBs. Numerous genetic aberrations, including mutations of TERT, DDX3X, and the PI3K/AKT/mTOR pathway are almost exclusive to adult patients. We elaborate on the newest development within the evolution of molecular subclassification, and compare proposed risk categories across emerging classification systems. We discuss discoveries based on preclinical models and elaborate on the applicability of potential new therapies, including BET bromodomain inhibitors, statins, inhibitors of SMO, AURK, PLK, cMET, targeting stem-like cells, and emerging immunotherapeutic strategies. An enormous amount of data on the genetic background of SHH-MB have accumulated, nevertheless, subgroup affiliation does not provide reliable prediction about response to therapy. Emerging subtypes within SHH-MB offer more layered risk stratifications. Rational clinical trial designs with the incorporation of available molecular knowledge are inevitable. Improved collaboration across the scientific community will be imperative for therapeutic breakthroughs.

Molecular markers and potential therapeutic targets in non-WNT/non-SHH (group 3 and group 4) medulloblastomas.

Childhood medulloblastomas (MB) are heterogeneous and are divided into four molecular subgroups. The provisional non-wingless-activated (WNT)/non-sonic hedgehog-activated (SHH) category combining group 3 and group 4 represents over two thirds of all MBs, coupled with the highest rates of metastases and least understood pathology. The molecular era expanded our knowledge about molecular aberrations involved in MB tumorigenesis, and here, we review processes leading to non-WNT/non-SHH MB formations.The heterogeneous group 3 and group 4 MBs frequently harbor rare individual genetic alterations, yet the emerging profiles suggest that infrequent events converge on common, potentially targetable signaling pathways. A mutual theme is the altered epigenetic regulation, and in vitro approaches targeting epigenetic machinery are promising. Growing evidence indicates the presence of an intermediate, mixed signature group along group 3 and group 4, and future clarifications are imperative for concordant classification, as misidentifying patient samples has serious implications for therapy and clinical trials.To subdue the high MB mortality, we need to discern mechanisms of disease spread and recurrence. Current preclinical models do not represent the full scale of group 3 and group 4 heterogeneity: all of existing group 3 cell lines are MYC-amplified and most mouse models resemble MYC-activated MBs. Clinical samples provide a wealth of information about the genetic divergence between primary tumors and metastatic clones, but recurrent MBs are rarely resected. Molecularly stratified treatment options are limited, and targeted therapies are still in preclinical development. Attacking these aggressive tumors at multiple frontiers will be needed to improve stagnant survival rates.

Demographic shift disproportionately increases cancer burden in an aging nation: current and expected incidence and mortality in Hungary up to 2030.

BACKGROUND: Population aging is a common demographic pattern in developed countries, and aging increases the risk of cancer. The disproportionately high cancer burden, as a consequence, is especially pronounced in Central and Eastern European countries, including Hungary. METHODS: We summarized current and projected future cancer incidences and mortalities utilizing data from the last two decades. Predictions are based on cancer incidence and mortality collected between 1996 and 2015 in Hungary. In addition to the crude rates, data were age standardized to the European standard population (ESP) of 2013, ESP of 1976, and local census of 2011. RESULTS: The lifetime probability of developing cancer and cancer-related mortality has already reached 56.9% and 27.6% in men, respectively, and 51.9% and 21.7% in women. Between 2016 and 2030, the total population is expected to shrink by 6%, while the number of 60-year olds and above will grow by 18%. This will lead to a 35% increase in cancer incidence and 30% increase in cancer death among 65-85-year olds. Joinpoint regression identified the period 2007-2015 as starting point for this coming increase in new cases. In women, lung and breast cancer will increase yearly by 1.9% and 1.7%, respectively, between 2016 and 2030, while in men, the prostate and colorectal cancer rates will increase yearly by 3.6% and 2.1%. CONCLUSION: In the aging population of Hungary, cancer incidence will increase considerably over previous projections. Although a large portion of the most rapidly rising cancers are avoidable by implementing public health programs, a substantial portion remains inevitably incurable.

Author Correction: Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Validation of miRNA prognostic power in hepatocellular carcinoma using expression data of independent datasets.

Multiple studies suggested using different miRNAs as biomarkers for prognosis of hepatocellular carcinoma (HCC). We aimed to assemble a miRNA expression database from independent datasets to enable an independent validation of previously published prognostic biomarkers of HCC. A miRNA expression database was established by searching the TCGA (RNA-seq) and GEO (microarray) repositories to identify miRNA datasets with available expression and clinical data. A PubMed search was performed to identify prognostic miRNAs for HCC. We performed a uni- and multivariate Cox regression analysis to validate the prognostic significance of these miRNAs. The Limma R package was applied to compare the expression of miRNAs between tumor and normal tissues. We uncovered 214 publications containing 223 miRNAs identified as potential prognostic biomarkers for HCC. In the survival analysis, the expression levels of 55 and 84 miRNAs were significantly correlated with overall survival in RNA-seq and gene chip datasets, respectively. The most significant miRNAs were hsa-miR-149, hsa-miR-139, and hsa-miR-3677 in the RNA-seq and hsa-miR-146b-3p, hsa-miR-584, and hsa-miR-31 in the microarray dataset. Of the 223 miRNAs studied, the expression was significantly altered in 102 miRNAs in tumors compared to normal liver tissues. In summary, we set up an integrated miRNA expression database and validated prognostic miRNAs in HCC.

Determining consistent prognostic biomarkers of overall survival and vascular invasion in hepatocellular carcinoma.

Background: Potential prognostic biomarker candidates for hepatocellular carcinoma (HCC) are abundant, but their generalizability is unexplored. We cross-validated markers of overall survival (OS) and vascular invasion in independent datasets. Methods: The literature search yielded 318 genes related to survival and 52 related to vascular invasion. Validation was performed in three datasets (RNA-seq, n = 371; Affymetrix arrays, n = 91; Illumina gene chips, n = 135) by uni- and multivariate Cox regression and Mann-Whitney U-test, separately for Asian and Caucasian patients. Results: One hundred and eighty biomarkers remained significant in Asian and 128 in Caucasian subjects at p < 0.05. After multiple testing correction BIRC5 (p = 1.9 × 10-10), CDC20 (p = 2.5 × 10-9) and PLK1 (p = 3 × 10-9) endured as best performing genes in Asian patients; however, none remained significant in the Caucasian cohort. In a multivariate analysis, significance was reached by stage (p = 0.0018) and expression of CENPH (p = 0.0038) and CDK4 (p = 0.038). KIF18A was the only gene predicting vascular invasion in the Affymetrix and Illumina cohorts (p = 0.003 and p = 0.025, respectively). Conclusion: Overall, about half of biomarker candidates failed to retain prognostic value and none were better than stage predicting OS. Impact: Our results help to eliminate biomarkers with limited capability to predict OS and/or vascular invasion.

Mutations Defining Patient Cohorts With Elevated PD-L1 Expression in Gastric Cancer.

The immunotherapy agent pembrolizumab has been approved for gastric cancer (GC) patients with recurrent or advanced disease who are PD-L1 positive. Mutations in the primary lesion may drive the expression of immune targets thereby priming the tumor to therapeutic sensitivity. In this study, we aimed to uncover mutations associated with elevated PD-L1 expression in GC patients. Data from 410 GC patients were available, including the mutational spectrum of 39,916 genes and expression values of 20,500 genes. PD-L1 gene expression was compared to the mutational status of each gene separately by using a Mann-Whitney U-test and a Receiver Operating Characteristic test. Only mutations with a prevalence over 5% were considered. Significance was accepted in cases of p < 1E-05 and a fold change over 1.44. Mutations in 209 genes were associated with increased PD-L1 expression. These mutations were enriched in genes related to microtubule-based movement (p = 3.4E-4), cell adhesion (p = 4.9E-4), response to DNA-damage (p = 6.9E-4), and double-strand break-repair (p = 1.6E-3). Mutations in TTK (p = 8.8E-10, AUC = 0.77), COL7A1 (p = 2.0E-9, AUC = 0.74), KIF15 (p = 2.5E-9, AUC = 0.75), and BDP1 (p = 3.3E-9, AUC = 0.74) had the strongest link to elevated PD-L1 expression. Finally, we established a decision tree based on mutations in PIK3CA, MEF2C, SLC11A1, and KIF15 capable to separate patient sub-cohorts with elevated PD-L1 expression. In summary, we identified mutations associated with elevated PD-L1 expression that facilitate the development of better prognostic biomarkers for GC, and might offer insight into the underlying tumor biology.