Molecular Classification of Endometrial Cancer and Its Impact on Therapy Selection.

Endometrial cancer (EC) accounts for 90% of uterine cancer cases. It is considered not only one of the most common gynecological malignancies but also one of the most frequent cancers among women overall. Nowadays, the differentiation of EC subtypes is based on immunohistochemistry and molecular techniques. It is considered that patients' prognosis and the implementation of the appropriate treatment depend on the cancer subtype. Patients with pathogenic variants in POLE have the most favorable outcome, while those with abnormal p53 protein have the poorest. Therefore, in patients with POLE mutation, the de-escalation of postoperative treatment may be considered, and patients with abnormal p53 protein should be subjected to intensive adjuvant therapy. Patients with a DNA mismatch repair (dMMR) deficiency are classified in the intermediate prognosis group as EC patients without a specific molecular profile. Immunotherapy has been recognized as an effective treatment method in patients with advanced or recurrent EC with a mismatch deficiency. Thus, different adjuvant therapy approaches, including targeted therapy and immunotherapy, are being proposed depending on the EC subtype, and international guidelines, such as those published by ESMO and ESGO/ESTRO/ESP, include recommendations for performing the molecular classification of all EC cases. The decision about adjuvant therapy selection has to be based not only on clinical data and histological type and stage of cancer, but, following international recommendations, has to include EC molecular subtyping. This review describes how molecular classification could support more optimal therapeutic management in endometrial cancer patients.

Deep learning-based tumor microenvironment segmentation is predictive of tumor mutations and patient survival in non-small-cell lung cancer.

BACKGROUND: Despite the fact that tumor microenvironment (TME) and gene mutations are the main determinants of progression of the deadliest cancer in the world - lung cancer, their interrelations are not well understood. Digital pathology data provides a unique insight into the spatial composition of the TME. Various spatial metrics and machine learning approaches were proposed for prediction of either patient survival or gene mutations from this data. Still, these approaches are limited in the scope of analyzed features and in their explainability, and as such fail to transfer to clinical practice. METHODS: Here, we generated 23,199 image patches from 26 hematoxylin-and-eosin (H&E)-stained lung cancer tissue sections and annotated them into 9 different tissue classes. Using this dataset, we trained a deep neural network ARA-CNN. Next, we applied the trained network to segment 467 lung cancer H&E images from The Cancer Genome Atlas (TCGA) database. We used the segmented images to compute human-interpretable features reflecting the heterogeneous composition of the TME, and successfully utilized them to predict patient survival and cancer gene mutations. RESULTS: We achieved per-class AUC ranging from 0.72 to 0.99 for classifying tissue types in lung cancer with ARA-CNN. Machine learning models trained on the proposed human-interpretable features achieved a c-index of 0.723 in the task of survival prediction and AUC up to 73.5% for PDGFRB in the task of mutation classification. CONCLUSIONS: We presented a framework that accurately predicted survival and gene mutations in lung adenocarcinoma patients based on human-interpretable features extracted from H&E slides. Our approach can provide important insights for designing novel cancer treatments, by linking the spatial structure of the TME in lung adenocarcinoma to gene mutations and patient survival. It can also expand our understanding of the effects that the TME has on tumor evolutionary processes. Our approach can be generalized to different cancer types to inform precision medicine strategies.

Failure of Immunotherapy-The Molecular and Immunological Origin of Immunotherapy Resistance in Lung Cancer.

Immune checkpoint inhibitors (ICIs) have a huge impact on clinical treatment results in non-small cell lung cancer (NSCLC). Blocking antibodies targeting programmed cell death protein 1 (PD-1), programmed cell death protein ligand 1 (PD-L1) or CTLA-4 (cytotoxic T cell antigen 4) have been developed and approved for the treatment of NSCLC patients. However, a large number of patients develop resistance to this type of treatment. Primary and secondary immunotherapy resistance are distinguished. No solid biomarkers are available that are appropriate to predict the unique sensitivity to immunotherapy. Knowledge of predictive markers involved in treatment resistance is fundamental for planning of new treatment combinations. Scientists focused research on the use of immunotherapy as an essential treatment in combination with other therapy strategies, which could increase cancer immunogenicity by generating tumor cells death and new antigen release as well as by targeting other immune checkpoints and tumor microenvironment. In the present review, we summarize the current knowledge of molecular bases underlying immunotherapy resistance and discuss the capabilities and the reason of different therapeutic combinations.

The Correlation of Mutations and Expressions of Genes within the PI3K/Akt/mTOR Pathway in Breast Cancer-A Preliminary Study.

There is an urgent need to seek new molecular biomarkers helpful in diagnosing and treating breast cancer. In this elaboration, we performed a molecular analysis of mutations and expression of genes within the PI3K/Akt/mTOR pathway in patients with ductal breast cancer of various malignancy levels. We recognized significant correlations between the expression levels of the studied genes. We also performed a bioinformatics analysis of the data available on the international database TCGA and compared them with our own research. Studies on mutations and expression of genes were conducted using High-Resolution Melt PCR (HRM-PCR), Allele-Specific-quantitative PCR (ASP-qPCR), Real-Time PCR molecular methods in a group of women with ductal breast cancer. Bioinformatics analysis was carried out using web source Ualcan and bc-GenExMiner. In the studied group of women, it was observed that the prevalence of mutations in the studied PIK3CA and AKT1 genes was 29.63%. It was stated that the average expression level of the PIK3CA, PIK3R1, PTEN genes in the group of breast cancer patients is lower in comparison to the control group, while the average expression level of the AKT1 and mTOR genes in the studied group was higher in comparison to the control group. It was also indicated that in the group of patients with mutations in the area of the PIK3CA and AKT1 genes, the PIK3CA gene expression level is statistically significantly lower than in the group without mutations. According to our knowledge, we demonstrate, for the first time, that there is a very strong positive correlation between the levels of AKT1 and mTOR gene expression in the case of patients with mutations and without mutations.

NRG1 Gene Fusions-What Promise Remains Behind These Rare Genetic Alterations? A Comprehensive Review of Biology, Diagnostic Approaches, and Clinical Implications.

Non-small cell lung cancer (NSCLC) presents a variety of druggable genetic alterations that revolutionized the treatment approaches. However, identifying new alterations may broaden the group of patients benefitting from such novel treatment options. Recently, the interest focused on the neuregulin-1 gene (NRG1), whose fusions may have become a potential predictive factor. To date, the occurrence of NRG1 fusions has been considered a negative prognostic marker in NSCLC treatment; however, many premises remain behind the targetability of signaling pathways affected by the NRG1 gene. The role of NRG1 fusions in ErbB-mediated cell proliferation especially seems to be considered as a main target of treatment. Hence, NSCLC patients harboring NRG1 fusions may benefit from targeted therapies such as pan-HER family inhibitors, which have shown efficacy in previous studies in various cancers, and anti-HER monoclonal antibodies. Considering the increased interest in the NRG1 gene as a potential clinical target, in the following review, we highlight its biology, as well as the potential clinical implications that were evaluated in clinics or remained under consideration in clinical trials.

Variant Allele Frequency Analysis of Circulating Tumor DNA as a Promising Tool in Assessing the Effectiveness of Treatment in Non-Small Cell Lung Carcinoma Patients.

Despite the different possible paths of treatment, lung cancer remains one of the leading causes of death in oncological patients. New tools guiding the therapeutic process are under scientific investigation, and one of the promising indicators of the effectiveness of therapy in patients with NSCLC is variant allele frequency (VAF) analysis. VAF is a metric characterized as the measurement of the specific variant allele proportion within a genomic locus, and it can be determined using methods based on NGS or PCR. It can be assessed using not only tissue samples but also ctDNA (circulating tumor DNA) isolated from liquid biopsy. The non-invasive characteristic of liquid biopsy enables a more frequent collection of material and increases the potential of VAF analysis in monitoring therapy. Several studies have been performed on patients with NSCLC to evaluate the possibility of VAF usage. The research carried out so far demonstrates that the evaluation of VAF dynamics may be useful in monitoring tumor progression, remission, and recurrence during or after treatment. Moreover, the use of VAF analysis appears to be beneficial in making treatment decisions. However, several issues require better understanding and standardization before VAF testing can be implemented in clinical practice. In this review, we discuss the difficulties in the application of ctDNA VAF analysis in clinical routine, discussing the diagnostic and methodological challenges in VAF measurement in liquid biopsy. We highlight the possible applications of VAF-based measurements that are under consideration in clinical trials in the monitoring of personalized treatments for patients with NSCLC.

Lipids balance as a spectroscopy marker of diabetes. Analysis of FTIR spectra by 2D correlation and machine learning analyses.

The number of people suffering from type 2 diabetes has rapidly increased. Taking into account, that elevated intracellular lipid concentrations, as well as their metabolism, are correlated with diminished insulin sensitivity, in this study we would like to show lipids spectroscopy markers of diabetes. For this purpose, serum collected from rats (animal model of diabetes) was analyzed using Fourier Transformed Infrared-Attenuated Total Reflection (FTIR-ATR) spectroscopy. Analyzed spectra showed that rats with diabetes presented higher concentration of phospholipids and cholesterol in comparison with non-diabetic rats. Moreover, the analysis of second (IInd) derivative spectra showed no structural changes in lipids. Machine learning methods showed higher accuracy for IInd derivative spectra (from 65 % to 89 %) than for absorbance FTIR spectra (53-65 %). Moreover, it was possible to identify significant wavelength intervals from IInd derivative spectra using random forest-based feature selection algorithm, which further increased the accuracy of the classification (up to 92 % for phospholipid region). Moreover decision tree based on the selected features showed, that peaks at 1016 cm-1 and 2936 cm-1 can be good candidates of lipids marker of diabetes.

The presence of HER2 exon 20 insertion in patients with central nervous system metastases from non-small lung cancer--a potential application in classification for therapy.

INTRODUCTION: HER2 (ErbB2/neu) is a member of the ErbB family of four structurally related receptors of tyrosine kinase activity. Overexpression of ErbB-1 (EGFR) and HER2 is found in many human cancers, but the presence of these genes mutations determines the effectiveness of EGFR and HER2 tyrosine kinase inhibitors in the therapy of non-small cell lung cancer (NSCLC). MATERIAL AND METHODS: To search for insertions of the HER2 gene in exon 20 in 150 brain metastases of non-small cell lung cancer patients, we used a PCR technique based on analysis of amplified DNA fragment lengths. We also compared the HER2 mutational status with clinicopathologic features and the presence of EGFR and BRAF mutations. RESULTS: HER2 mutation was present in one male, non-smoking patient with low differentiated adenocarcinoma (0.67% of all patients and 1.5% of patients with adenocarcinoma). The mutations of EGFR and BRAF genes were not found in HER2-mutated patient. CONCLUSIONS: The literature data suggests that patients with HER2 mutations may be sensitive to tyrosine kinase inhibitors of both EGFR and HER2 receptors (e.g. afatinib). Therefore, the identification of new driver mutations in NSCLC can improve the quality of patient care by enabling the use of correct molecularly targeted therapies.

Mechanisms of resistance to reversible inhibitors of EGFR tyrosine kinase in non-small cell lung cancer.

Abnormalities of epidermal growth factor receptor (EGFR) in non-small-cell lung cancer (NSCLC) patients consist of EGFR overexpression and EGFR (HER1) gene mutations. Structural dysfunction of the tyrosine kinase domain of EGFR is associated with the clinical response to tyrosine kinase inhibitors (TKI) in patients with NSCLC. The most common EGFR gene mutations occur as either deletions in exon 19 or as substitution L858R in exon 21 and cause a clinically beneficial response to gefinitib or erlotinib treatment. Unfortunately, the majority of patients finally develop resistance to these drugs. Acquired resistance is linked to secondary mutations localised in the EGFR gene, mainly substitution T790M in exon 20. Through intense research a few different mechanisms of resistance to reversible tyrosine kinase inhibitors have been identified: amplification of MET or IGF-1R genes, abnormalities of PTEN and mTOR proteins as well as rare mutations in EGFR and HER2 genes. Extensively investigated new drugs could be of significant efficiency in NSCLC patients with secondary resistance to reversible EGFR TKI.

Genetic Clonality as the Hallmark Driving Evolution of Non-Small Cell Lung Cancer.

Data indicate that many driver alterations from the primary tumor of non-small cell lung cancer (NSCLC) are predominantly shared across all metastases; however, disseminating cells may also acquire a new genetic landscape across their journey. By comparing the constituent subclonal mutations between pairs of primary and metastatic samples, it is possible to derive the ancestral relationships between tumor clones, rather than between tumor samples. Current treatment strategies mostly rely on the theory that metastases are genetically similar to the primary lesions from which they arise. However, intratumor heterogeneity (ITH) affects accurate diagnosis and treatment decisions and it is considered the main hallmark of anticancer therapy failure. Understanding the genetic changes that drive the metastatic process is critical for improving the treatment strategies of this deadly condition. Application of next generation sequencing (NGS) techniques has already created knowledge about tumorigenesis and cancer evolution; however, further NGS implementation may also allow to reconstruct phylogenetic clonal lineages and clonal expansion. In this review, we discuss how the clonality of genetic alterations influence the seeding of primary and metastatic lesions of NSCLC. We highlight that wide genetic analyses may reveal the phylogenetic trajectories of NSCLC evolution, and may pave the way to better management of follow-up and treatment.

The Overview of Perspectives of Clinical Application of Liquid Biopsy in Non-Small-Cell Lung Cancer.

The standard diagnostics procedure for non-small-cell lung cancer (NSCLC) requires a pathological evaluation of tissue samples obtained by surgery or biopsy, which are considered invasive sampling procedures. Due to this fact, re-sampling of the primary tumor at the moment of progression is limited and depends on the patient's condition, even if it could reveal a mechanism of resistance to applied therapy. Recently, many studies have indicated that liquid biopsy could be provided for the noninvasive management of NSCLC patients who receive molecularly targeted therapies or immunotherapy. The liquid biopsy of neoplastic patients harbors small fragments of circulating-free DNA (cfDNA) and cell-free RNA (cfRNA) secreted to the circulation from normal cells, as well as a subset of tumor-derived circulating tumor cells (CTCs) or circulating tumor DNA (ctDNA). In NSCLC patients, a longitudinal assessment of genetic alterations in "druggable" genes in liquid biopsy might improve the follow-up of treatment efficacy and allow for the detection of an early progression before it is detectable in computed tomography or a clinical image. However, a liquid biopsy may be used to determine a variety of relevant molecular or genetic information for understanding tumor biology and its evolutionary trajectories. Thus, liquid biopsy is currently associated with greater hope for common diagnostic and clinical applications. In this review, we would like to highlight diagnostic challenges in the application of liquid biopsy into the clinical routine and indicate its implications on the metastatic spread of NSCLC or monitoring of personalized treatment regimens.

Genomic Profiling Identifies Putative Pathogenic Alterations in NSCLC Brain Metastases.

Introduction: Brain metastases (BM) severely affect the prognosis and quality of life of patients with NSCLC. Recently, molecularly targeted agents were found to have promising activity against BM in patients with NSCLC whose primary tumors carry "druggable" mutations. Nevertheless, it remains critical to identify specific pathogenic alterations that drive NSCLC-BM and that can provide novel and more effective therapeutic targets. Methods: To identify potentially targetable pathogenic alterations in NSCLC-BM, we profiled somatic copy number alterations (SCNAs) in 51 matched pairs of primary NSCLC and BM samples from 33 patients with lung adenocarcinoma and 18 patients with lung squamous cell carcinoma. In addition, we performed multiregion copy number profiling on 15 BM samples and whole-exome sequencing on 40 of 51 NSCLC-BM pairs. Results: BM consistently had a higher burden of SCNAs compared with the matched primary tumors, and SCNAs were typically homogeneously distributed within BM, suggesting BM do not undergo extensive evolution once formed. By comparing focal SCNAs in matched NSCLC-BM pairs, we identified putative BM-driving alterations affecting multiple cancer genes, including several potentially targetable alterations in genes such as CDK12, DDR2, ERBB2, and NTRK1, which we validated in an independent cohort of 84 BM samples. Finally, we identified putative pathogenic alterations in multiple cancer genes, including genes involved in epigenome editing and 3D genome organization, such as EP300, CTCF, and STAG2, which we validated by targeted sequencing of an independent cohort of 115 BM samples. Conclusions: Our study represents the most comprehensive genomic characterization of NSCLC-BM available to date, paving the way to functional studies aimed at assessing the potential of the identified pathogenic alterations as clinical biomarkers and targets.

Somatic Copy Number Alterations in Human Cancers: An Analysis of Publicly Available Data From The Cancer Genome Atlas.

Somatic copy number alterations (SCNAs) are a pervasive trait of human cancers that contributes to tumorigenesis by affecting the dosage of multiple genes at the same time. In the past decade, The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) initiatives have generated and made publicly available SCNA genomic profiles from thousands of tumor samples across multiple cancer types. Here, we present a comprehensive analysis of 853,218 SCNAs across 10,729 tumor samples belonging to 32 cancer types using TCGA data. We then discuss current models for how SCNAs likely arise during carcinogenesis and how genomic SCNA profiles can inform clinical practice. Lastly, we highlight open questions in the field of cancer-associated SCNAs.

Effect of TOP2A and ERCC1 gene polymorphisms on the efficacy and toxicity of cisplatin and etoposide-based chemotherapy in small cell lung cancer patients.

INTRODUCTION: The main treatment regimen for small cell lung cancer (SCLC) involves platinum-based chemotherapy (cisplatin or carboplatin) and etoposide. Single nucleotide polymorphisms (SNPs) in TOP2A and ERCC1 genes were tested as prognostic and predictive factors in non-small cell lung cancer (NSCLC). There are limited data about the clinical relevance of these genetic alterations in SCLC. We undertook this retrospective study to determine the influence of SNPs in TOP2A (rs34300454; rs13695; rs11540720) and ERCC1 (rs11615; rs3212986) genes on the efficiency and toxicity of chemotherapy with platinum and etoposide in SCLC Caucasian patients. MATERIAL AND METHODS: The studied group included 103 Caucasian SCLC patients (65 male, 38 female, median age 65 ±7.5 years). Detailed clinical-demographical data were collected and response to treatment was monitored. DNA was isolated from peripheral blood leukocytes using QIAamp DNA Mini Kit. Single nucleotide polymorphisms were analyzed using TaqMan hydrolyzing probes in real-time PCR technique on an Eco Illumina device. RESULTS: Patients with C/C genotype in rs13695 of the TOP2A gene had significantly lower risk of neutropenia during chemotherapy than C/T heterozygous patients (p = 0.02, χ² = 5.51, OR = 2.676, 95% CI: 1.165-6.143). Patients harbouring homozygous C/C genotype in rs3212986 of the ERCC1 gene had significantly higher risk of anaemia during chemotherapy, than heterozygous C/A patients (p = 0.045, χ² = 4.01, OR = 0.417, 95% CI: 0.175-0.991). Furthermore, heterozygous G/A genotype in rs11615 of the ERCC1 gene was associated with significant shortening of OS (9 vs. 12 months) compared to homozygous A/A genotype (p = 0.01, χ² = 6.31, HR = 1.657, 95% CI: 1.0710-2.5633). CONCLUSIONS: SNPs in ERCC1 and TOP2 genes may be associated with the toxicities and survival of SCLC patients treated with cisplatin and etoposide.

Lung Cancer Immunotherapy in Transplant Patients and in Patients With Autoimmune Diseases.

The use of immune checkpoint inhibitors (ICIs) delivered great and new possibilities in modern treatment of many types of cancers. This therapy based on blockade of such molecules as CTLA-4 (cytotoxic T lymphocyte-associated antigen), PD-1 (programmed cell death receptor type 1), or PD-1 ligand (PD-L1) brings a new hope for patients with non-small cell lung cancer (NSCLC), melanoma, or head and neck squamous carcinoma. Efficacy of immunotherapy was proven in many clinical trials. Unfortunately, ICIs treatment was not addressed to the patients with preexisting allogeneic transplants or autoimmune diseases mainly due to high risk of transplant rejection, exacerbation of autoimmune diseases, and risk of serious toxicity. However, it is possible to receive anti-tumor response to ICIs treatment avoiding graft rejection by adjusting the immunosuppression. Obviously, it depends on the type of transplants: the use of immunotherapy is usually possible in kidney or corneal recipients, but it could be difficult in patients with liver and heart transplant. Therefore, the development of biomarkers for tumor response and transplant rejection in ICIs treated patients is essential. Data coming from published literature support the possibilities of using ICIs in patients with preexisting autoimmune diseases who undergoing proper management of side effects of immunotherapy or when the potential benefits of such treatment outweigh the potential risks. This depends on the type of autoimmune disease and may be difficult or not feasible in patients with systemic lupus erythematosus or systemic sclerosis. Therefore, it may be appropriate to include cancer patients with preexisting autoimmune disease or with allogeneic transplants in clinical trials using immunotherapy when no other effective cancer treatment options exist.

The Role of Intratumor Heterogeneity in the Response of Metastatic Non-Small Cell Lung Cancer to Immune Checkpoint Inhibitors.

Immune checkpoint inhibitors (ICIs) represent one of the most promising therapeutic approaches in metastatic non-small cell lung cancer (M-NSCLC). Unfortunately, approximately 50-75% of patients do not respond to this treatment modality. Intratumor heterogeneity (ITH) at the genetic and phenotypic level is considered as a major cause of anticancer therapy failure, including resistance to ICIs. Recent observations suggest that spatial heterogeneity in the composition and spatial organization of the tumor microenvironment plays a major role in the response of M-NSCLC patients to ICIs. In this mini review, we first present a brief overview of the use of ICIs in M-NSCLC. We then discuss the role of genetic and non-genetic ITH on the efficacy of ICIs in patients with M-NSCLC.

Promoter polymorphisms of TOP2A and ERCC1 genes as predictive factors for chemotherapy in non-small cell lung cancer patients.

BACKGROUND: Topoisomerase 2-alpha (TOP2A) is an enzyme that controls topologic changes in DNA during transcription and replication. ERCC1 is an enzyme that takes part in DNA repair processes. The purpose of this study was to assess the predictive role of particular single nucleotide polymorphisms (SNPs) in the promoter regions of TOP2A and ERCC1 genes in non-small cell lung cancer patients (NSCLC) treated with chemotherapy. MATERIALS AND METHODS: We enrolled 113 NSCLC patients treated in the first line with platinum-based chemotherapy. Effectiveness was available for 71 patients. DNA was isolated from whole blood using the Qiamp DNA Blood Mini kit (Qiagen). We examined five SNPs: rs11615 (ERCC1), rs3212986 (ERCC1), rs13695 (TOP2A), rs34300454 (TOP2A), rs11540720 (TOP2A). Quantitative PCR using the TaqMan probe (ThermoFisher) was performed on a Eco Illumina Real-Time PCR system device (Illumina Inc). RESULTS: Patients with the A/A genotype in rs11615 of the ERCC1 gene had significantly longer median progression free survival (PFS) (8.5 months; P = .0088). Patients with the C/C genotype in rs3212986 of the ERCC1 gene had longer median PFS (7 months; P = .05). Patients with the C/C genotype in rs34300454 of TOP2A gene had significantly higher median PFS (7.5 months; P = .0029). Carriers of the C/C genotype in rs34300454 of the TOP2A gene had significantly longer median OS (15.5 months; P = .0017). Patients with the A/A genotype in rs11615 of the ERCC1 gene had significantly higher risk of neutropenia (P = .0133). CONCLUSIONS: Polymorphisms of the TOP2A and ERCC1 genes may be a predictive factor of toxicities and survival for chemotherapy in NSCLC patients.

Analysis of KRAS, NRAS, BRAF, and PIK3CA mutations could predict metastases in colorectal cancer: A preliminary study.

BACKGROUND: Colorectal cancer (CRC) is usually diagnosed in the metastatic stage, when chemotherapy and molecularly-targeted therapies, instead of surgery, play the most important therapeutic role. Application of anti-epidermal growth factor receptor (EGFR) therapy requires the analysis of RAS mutation status and only RAS wild-type (wt) patients are qualified for the therapy. OBJECTIVES: The objective of this study was to analyze driver mutations in KRAS, NRAS, BRAF, and PIK3CA genes in CRC patients. MATERIAL AND METHODS: We assessed the KRAS, NRAS, BRAF, and PIK3CA genes in 102 inoperable, locally advanced and advanced CRC patients. Real-time polymerase chain reaction (RT-PCR) and high resolution melt PCR (HRM-PCR) techniques with DNA intercalating dye were applied in the study. RESULTS: Forty-six patients demonstrated the presence of examined mutations (45.1%). No significant differences in driver mutation occurrence between men and women, as well as between younger (<65 years) and older (≥65 years) patients were found. The mutations were present significantly more frequently in metastatic than in primary tumors (p = 0.039) due to the high incidence of KRAS gene mutations in metastatic tissue. BRAF and PIK3CA mutations were found only in primary tumors. The incidence of PIK3CA mutations was significantly higher (11.77%) in early than in advanced stages of the disease (1.96%; p = 0.05); NRAS mutations were found only in metastatic cancer (7.85%; p = 0.041). Only a single mutation of the PIK3CA and no mutations of NRAS were found in rectal cancer. CONCLUSIONS: Our results have shown low occurrence of driver mutations in Polish CRC patients, involving also mutations in rarely tested genes. The extent of the research panel of additional mutations could contribute to creating a better method of qualifying patients for molecularly targeted therapies and obtaining a better outcome for these therapeutic strategies.

MicroRNAs aid the assessment of programmed death ligand 1 expression in patients with non-small cell lung cancer.

The qualification of patients with non-small cell lung cancer (NSCLC) for anti-programmed cell death 1 (PD-1) or anti-programmed death ligand 1 (PD-L1) antibody therapy is based on an immunohistochemistry (IHC) assessment of PD-L1 expression. Immunological checkpoint inhibitors improve the overall survival of patients with expression of PD-L1; however certain PD-L1-negative patients may also benefit from immunotherapy. This indicates the requirement for novel predictive factors for the qualification of immunotherapy. It is also necessary to understand the mechanisms that effect the expression of PD-L1 in tumor cells. The expression of PD-L1 in 47 formalin-fixed, paraffin-embedded, NSCLC specimens was assessed using IHC and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The expression of 8 microRNAs (miRNAs, miRs) complementary to PD-L1-mRNA was also evaluated using RT-qPCR. A positive correlation was revealed between the expression level of PD-L1-mRNA and 2 miRs, miR-141 (R=0.533; P=0.0029) and miR-1184 (R=0.463; P=0.049). There was also a positive correlation between the percentage of PD-L1-positive tumor cells and the expression levels of miR-141 (R=0.441; P=0.0024), miR-200b (R=0.372; P=0.011) and miR-429 (R=0.430; P=0.0028), and between the percentage of the tumor area with immune cell infiltration and the expression levels of miR-141 (R=0.333; P=0.03) and miR-200b (R=0.312; P=0.046). Additionally, the percentage of tumor cells expressing PD-L1 positively correlated with miR-141 expression (R=0.407; P=0.0055). Correlations between the expression of the investigated miRs (particularly miR-141) and PD-L1 indicated that miRs may regulate PD-L1 expression at a post-transcriptional level.