Heterogeneity of biomarker expression in non-small cell lung cancer

L’èxit de de la medicina de precisió en oncologia depèn, en gran mesura, d’una adequada selecció dels pacients que rebran teràpies dirigides contra dianes específiques del seu tumor. Per poder seleccionar els pacients, és indispensable disposar de biomarcadors amb valor predictiu que informin les decisions terapèutiques. MET i PD-L1 són dos receptors de membrana rellevants en la biologia del carcinoma pulmonar no microcític (CPNM). MET és un oncogen i l’activació de la seva via es troba relacionada amb múltiples processos pro-tumorals com són la proliferació i la motilitat cel·lulars, així com la invasió d’estructures veïnes. PD-L1 és una molècula clau en la resposta immunitàries, i la seva sobre-expressió en els tumors està relacionada amb la capacitat de les cèl·lules tumorals d’evitar el seu reconeixement i destrucció per part del sistema immunitari. Actualment, existeixen teràpies específiques dirigides contra aquestes molècules. L’estratègia més emprada per seleccionar els pacients que se’n poden beneficiar és la determinació de l’expressió d’ambdues molècules en teixit tumoral. Tanmateix, el valor de MET i de PD-L1 com a biomarcadors predictius i el mètode pel qual s’han de determinar és subjecte de debat. Estudis recents han detectat un alt grau d’heterogeneïtat genòmica en mostres tumorals en CPNM. Aquesta heterogeneïtat podria afectar de forma rellevant la classificació de pacients basada en l’expressió de biomarcadors. A més, aquest fet seria especialment rellevant en el cas del CPNM, ja que l’estudi de biomarcadors es fa generalment en mostres petites de teixit, provinents de biòpsies o citologies obtingudes mitjançant tècniques mínimament invasives. L’objectiu principal dels treballs presentats en aquesta tesi és estudiar l’heterogeneïtat de l’expressió de MET i PD-L1 en mostres de CPNM. Amb aquesta finalitat, hem analitzat mostres tumorals procedents de pacients tractats quirúrgicament de CPNM a l’Hospital del Mar. De cada tumor, hem seleccionat múltiples àrees geogràficament separades, les quals hem analitzat de forma independent. En l’estudi en que hem avaluat MET hem seleccionat quatre àrees per cada pacient, mentre que en l’estudi de PD-L1 n’hem seleccionat dues. En cada àrea tumoral, hem mesurat l’expressió de MET i de PD-L1 mitjançant mètodes d’immunohistoquímica i d’hibridació in situ fluorescent (FISH). Finalment, hem comparat l’expressió de MET i de PD-L1 entre diferents àrees tumorals. En el cas de MET, hem trobat discordances entre diferents àrees tumorals en un 20-40% per immunohistoquímica i en un 25-50% per FISH. En el cas de PD-L1, aquesta discordança ha estat major si es valora només l’expressió en limfòcits infiltrants de tumor (17-27%) que si es valora en cèl·lules tumorals (10-19%). A més, un 36% dels casos amb amplificació del gen que codifica PD-L1 determinada per FISH presenten aquesta amplificació només en una de les dues àrees analitzades. En conjunt, els nostres resultats suggereixen que l’expressió d’ambdós biomarcadors és heterogènia, tant si es mesura mitjançant immunohistoqumímica com mitjançant FISH. Aquesta heterogeneïtat pot tenir un impacte potencial en la classificació de tumors basada en l’expressió de biomarcadors i per tant, pot suposar una dificultat afegida a l’hora de desenvolupar teràpies dirigides per pacients amb CPNM.The success of precision medicine in oncology is dependent to a large extent on an adequate selection of patients who will receive targeted therapies aimed at specific molecular traits of their tumor. In order to be able conduct such patient selection, predictive biomarkers that can inform therapeutic decisions are essential. MET and PD-L1 are two relevant membrane receptors for non-small cell lung cancer (NSCLC) biology. MET is an oncogene the activation of which is involved in multiple pro-tumorigenic processes such as cell proliferation, motility and invasion. PD-L1 is a key molecule that acts during the immune response, and its overexpression in tumors is thought to mediate the ability of tumor cells to avoid immune cell recognition and destruction. Currently, there are specific therapies directed against these molecules. The most commonly used strategy to select the patients that will benefit from such drugs is the analysis of the expression of both molecules in tumor tissue. However, the value of MET and PD-L1 as predictive biomarkers and the method by which it should be determined is a subject of debate. Recent studies have detected a high degree of genomic heterogeneity in NSCLC tumor samples. This heterogeneity could significantly affect biomarker-based patient classification especially in the case of NSCLC, since biomarker studies are usually performed in small biopsies or cytology samples obtained through minimally invasive techniques. The main objective of the work presented in this thesis is to study the heterogeneity of the expression of MET and PD-L1 in NSCLC samples. For this purpose, we have analyzed tumor samples from NSCLC patients that had undergone surgical treatment at Hospital del Mar. Of each tumor, we have selected multiple geographically separate areas, which we analyzed independently. In the study evaluating MET, we selected four tumor areas per patient, while in the study evaluating PD-L1 we selected two areas. In each tumor area, we measured the expression MET and PD-L1 using immunohistochemical and fluorescence in situ hybridization methods (FISH). Finally, we compared the expression of MET and PD-L1 in different tumor areas. Regarding MET, we have found discordances between different tumor areas in 20-40% of cases using immunohistochemistry and in 25-50% of cases using FISH. Regarding PD-L1, this discrepancy was greater if we evaluated PD-L1 expression in tumor infiltrating lymphocytes (17-27%) than if we did so only in tumor cells (10-19%). Moreover, 36% of the cases with amplification of the gene coding for PD-L1 determined by FISH presented gene amplification only in one of the two areas analyzed. Overall, our results suggest that the expression of both biomarkers is heterogeneous, whether measured by immunohistochemistry or by FISH. This heterogeneity can have a potential impact on the classification of tumors based on the expression of biomarkers and, therefore, could represent a hurdle for the development of targeted therapies for NSCLC patients

Heterogeneity of biomarker expression in non-small cell lung cancer /

L'èxit de de la medicina de precisió en oncologia depèn, en gran mesura, d'una adequada selecció dels pacients que rebran teràpies dirigides contra dianes específiques del seu tumor. Per poder seleccionar els pacients, és indispensable disposar de biomarcadors amb valor predictiu que informin les decisions terapèutiques. MET i PD-L1 són dos receptors de membrana rellevants en la biologia del carcinoma pulmonar no microcític (CPNM). MET és un oncogen i l'activació de la seva via es troba relacionada amb múltiples processos pro-tumorals com són la proliferació i la motilitat cel·lulars, així com la invasió d'estructures veïnes. PD-L1 és una molècula clau en la resposta immunitàries, i la seva sobre-expressió en els tumors està relacionada amb la capacitat de les cèl·lules tumorals d'evitar el seu reconeixement i destrucció per part del sistema immunitari. Actualment, existeixen teràpies específiques dirigides contra aquestes molècules. L'estratègia més emprada per seleccionar els pacients que se'n poden beneficiar és la determinació de l'expressió d'ambdues molècules en teixit tumoral. Tanmateix, el valor de MET i de PD-L1 com a biomarcadors predictius i el mètode pel qual s'han de determinar és subjecte de debat. Estudis recents han detectat un alt grau d'heterogeneïtat genòmica en mostres tumorals en CPNM. Aquesta heterogeneïtat podria afectar de forma rellevant la classificació de pacients basada en l'expressió de biomarcadors. A més, aquest fet seria especialment rellevant en el cas del CPNM, ja que l'estudi de biomarcadors es fa generalment en mostres petites de teixit, provinents de biòpsies o citologies obtingudes mitjançant tècniques mínimament invasives. L'objectiu principal dels treballs presentats en aquesta tesi és estudiar l'heterogeneïtat de l'expressió de MET i PD-L1 en mostres de CPNM. Amb aquesta finalitat, hem analitzat mostres tumorals procedents de pacients tractats quirúrgicament de CPNM a l'Hospital del Mar. De cada tumor, hem seleccionat múltiples àrees geogràficament separades, les quals hem analitzat de forma independent. En l'estudi en que hem avaluat MET hem seleccionat quatre àrees per cada pacient, mentre que en l'estudi de PD-L1 n'hem seleccionat dues. En cada àrea tumoral, hem mesurat l'expressió de MET i de PD-L1 mitjançant mètodes d'immunohistoquímica i d'hibridació in situ fluorescent (FISH). Finalment, hem comparat l'expressió de MET i de PD-L1 entre diferents àrees tumorals. En el cas de MET, hem trobat discordances entre diferents àrees tumorals en un 20-40% per immunohistoquímica i en un 25-50% per FISH. En el cas de PD-L1, aquesta discordança ha estat major si es valora només l'expressió en limfòcits infiltrants de tumor (17-27%) que si es valora en cèl·lules tumorals (10-19%). A més, un 36% dels casos amb amplificació del gen que codifica PD-L1 determinada per FISH presenten aquesta amplificació només en una de les dues àrees analitzades. En conjunt, els nostres resultats suggereixen que l'expressió d'ambdós biomarcadors és heterogènia, tant si es mesura mitjançant immunohistoqumímica com mitjançant FISH. Aquesta heterogeneïtat pot tenir un impacte potencial en la classificació de tumors basada en l'expressió de biomarcadors i per tant, pot suposar una dificultat afegida a l'hora de desenvolupar teràpies dirigides per pacients amb CPNM.The success of precision medicine in oncology is dependent to a large extent on an adequate selection of patients who will receive targeted therapies aimed at specific molecular traits of their tumor. In order to be able conduct such patient selection, predictive biomarkers that can inform therapeutic decisions are essential. MET and PD-L1 are two relevant membrane receptors for non-small cell lung cancer (NSCLC) biology. MET is an oncogene the activation of which is involved in multiple pro-tumorigenic processes such as cell proliferation, motility and invasion. PD-L1 is a key molecule that acts during the immune response, and its overexpression in tumors is thought to mediate the ability of tumor cells to avoid immune cell recognition and destruction. Currently, there are specific therapies directed against these molecules. The most commonly used strategy to select the patients that will benefit from such drugs is the analysis of the expression of both molecules in tumor tissue. However, the value of MET and PD-L1 as predictive biomarkers and the method by which it should be determined is a subject of debate. Recent studies have detected a high degree of genomic heterogeneity in NSCLC tumor samples. This heterogeneity could significantly affect biomarker-based patient classification especially in the case of NSCLC, since biomarker studies are usually performed in small biopsies or cytology samples obtained through minimally invasive techniques. The main objective of the work presented in this thesis is to study the heterogeneity of the expression of MET and PD-L1 in NSCLC samples. For this purpose, we have analyzed tumor samples from NSCLC patients that had undergone surgical treatment at Hospital del Mar. Of each tumor, we have selected multiple geographically separate areas, which we analyzed independently. In the study evaluating MET, we selected four tumor areas per patient, while in the study evaluating PD-L1 we selected two areas. In each tumor area, we measured the expression MET and PD-L1 using immunohistochemical and fluorescence in situ hybridization methods (FISH). Finally, we compared the expression of MET and PD-L1 in different tumor areas. Regarding MET, we have found discordances between different tumor areas in 20-40% of cases using immunohistochemistry and in 25-50% of cases using FISH. Regarding PD-L1, this discrepancy was greater if we evaluated PD-L1 expression in tumor infiltrating lymphocytes (17-27%) than if we did so only in tumor cells (10-19%). Moreover, 36% of the cases with amplification of the gene coding for PD-L1 determined by FISH presented gene amplification only in one of the two areas analyzed. Overall, our results suggest that the expression of both biomarkers is heterogeneous, whether measured by immunohistochemistry or by FISH. This heterogeneity can have a potential impact on the classification of tumors based on the expression of biomarkers and, therefore, could represent a hurdle for the development of targeted therapies for NSCLC patients

Is there a role for epidermal growth factor receptor tyrosine kinase inhibitors in epidermal growth factor receptor wild-type non-small cell lung cancer?

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer with a world-wide annual incidence of around 1.3 million. The majority of patients are diagnosed with advanced disease and survival remains poor. However, relevant advances have occurred in recent years through the identification of biomarkers that predict for benefit of therapeutic agents. This is exemplified by the efficacy of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors for the treatment of EGFR mutant patients. These drugs have also shown efficacy in unselected populations but this point remains controversial. Here we have reviewed the clinical data that demonstrate a small but consistent subgroup of EGFR wild-type patients with NSCLC that obtain a clinical benefit from these drugs. Moreover, we review the biological rationale that may explain this benefit observed in the clinical setting

The prognostic role of epigenetic dysregulation in bladder cancer: A systematic review

BACKGROUND: Despite adequate treatment and follow-up, around one fifth of patients with localized bladder cancer will present with disease progression. Adequate prognostic biomarkers are lacking to define patients who are at risk. Mutations in chromatin remodeling genes are more frequently found in bladder cancer than in any other solid tumor. However, the prognostic relevance of epigenetic dysregulation has not been established and may offer an opportunity for biomarker discovery. METHODS: Looking for prognostic epigenetic factors, we performed a comprehensive PubMed search using keywords such as "bladder cancer", "chromatin remodeling", "gene methylation" and "epigenetics". We only included studies reporting on the association of epigenetic markers with prognostic outcomes such as recurrence, progression or survival. RESULTS: Of 1113 results, 87 studies met the inclusion criteria, which represented a total of 85 epigenetic markers with potential prognostic relevance. No prospective studies were identified. Seventy-three percent (64/87) of the studies involved mixed cohorts of muscle invasive and non-muscle invasive bladder cancer. Promoter methylation of genes with putative prognostic value affected cellular processes such as cell cycle, apoptosis, cell-adhesion or migration, as well as critical pathways such as MAP-kinase or Wnt. Alteration of chromatin regulatory elements suggest a prognostic relevance alterations leading to a predominantly silenced chromatin state. CONCLUSIONS: The prognostic impact of epigenetic alterations in bladder cancer is still unclear. Prospective evaluation of methylation marks and chromatin remodeling gene alterations using consistent methods and criteria is warranted

Immune microenvironment of triple-negative breast cancer in African-American and Caucasian women

PURPOSE: African-American (AA) patients with triple-negative breast cancer (TNBC) are less likely to achieve pathologic complete response from neoadjuvant chemotherapy and have poorer prognosis than Caucasian patients with TNBC, suggesting potential biological differences by race. Immune infiltration is the most consistent predictive marker for chemotherapy response and improved prognosis in TNBC. In this study, we test the hypothesis that the immune microenvironment differs between AA and Caucasian patients. METHODS: RNA-seq expression data were obtained from The Cancer Genome Atlas (TCGA) database for 162 AA and 697 Caucasian breast cancers. Estrogen receptor (ER)-positive, human epidermal growth factor receptor-2 (HER2)-positive, and TNBC subtypes were included in the analyses. Tumor infiltrating lymphocyte (TIL) counts, immunomodulatory scores, and molecular subtypes were obtained from prior publications for a subset of the TNBC cases. Differences in immune cell distributions and immune functions, measured through gene expression and TIL counts, as well as neoantigen, somatic mutation, amplification, and deletion loads, were compared by race and tumor subtype. RESULTS: Immune metagene analysis demonstrated marginal immune attenuation in AA TNBC relative to Caucasian TNBC that did not reach statistical significance. The distributions of immune cell populations, lymphocyte infiltration, molecular subtypes, and genomic aberrations between AA and Caucasian subtypes were also not significantly different. The MHC1 metagene demonstrated increased expression in AA ER-positive cancers relative to Caucasian ER-positive cancers. CONCLUSIONS: This study suggests that the immunological differences between AA and Caucasian breast cancers represented by TCGA data are subtle, if they exist at all. We observed no consistent racial differences in immune gene expression or TIL counts in TNBC by race. However, this study cannot rule out small differences in immune cell subtype distribution and activity status that may not be apparent in bulk RNA analysis

Quantification of specific antibodies against SARS-CoV-2 in breast milk of lactating women vaccinated with an mRNA vaccine

This cohort study assesses the concentration of SARS-CoV-2 antibodies in the breast milk of women who received vaccines for COVID-19 and their correlation with serum antibody levels

Quantification and progress over time of specific antibodies against severe acute respiratory syndrome coronavirus 2 in breast milk of lactating women vaccinated with BNT162b2 Pfizer-BioNTech coronavirus disease 2019 vaccine (LacCOVID)

Background: several observational studies demonstrated the passage of postvaccine antibodies through breast milk in women vaccinated against coronavirus disease 2019 (COVID-19), mostly with messenger RNA (mRNA)-based vaccines, but lacked long-term data. Methods: a 6-month prospective cohort study was performed to determine severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine-induced antibody levels in the breast milk of 33 lactating healthcare workers at different timepoints after mRNA BNT162b2 Pfizer-BioNTech COVID-19 vaccination. Moreover, we examined the correlation of SARS-CoV-2 antibody levels between serum and breast milk, adverse events related to vaccination, and rate of SARS-CoV-2 infections. Results: mothers' median age was 38 (interquartile range [IQR], 36-39) years and 15 (IQR, 10-22) months for infants. Median (IQR) SARS-CoV-2 immunoglobulin G (IgG) spike protein subunit S1 (S1) vaccine-induced levels at different timepoints for serum-milk pairs were 519 (234-937) to 1 (0-2.9) arbitrary units (AU)/mL at 2 weeks after first dose and 18 644 (9923-29 264) to 78 (33.7-128), 12 478 (6870-20 801) to 50.4 (24.3-104), 4094 (2413-8480) to 19.9 (10.8-51.9), 1350 (831-2298) to 8.9 (7.8-31.5) AU/mL at 2, 4, 12 and 24 weeks after second dose, respectively. We observed a positive correlation of antibody levels between serum and breast milk, no serious adverse events related to vaccination, and 2 (6%) COVID-19 vaccine breakthrough infections. Conclusions: women vaccinated with Pfizer-BioNTech transmit antibodies into breast milk with a positive correlation with serum levels. Both decreased over time in a 6-month follow-up

Comparison of different methods for defining hyperprogressive disease in NSCLC

Introduction: Hyperprogressive disease (HPD) as a consequence of immune checkpoint inhibitors in NSCLC has been reported in multiple studies. However, inconsistent results in incidence and survival outcomes within studies, together with different assessment methods, have led to increasing controversy regarding the concept of HPD. Methods: Consecutive patients treated with nivolumab (N = 42) or docetaxel (N = 37) were evaluated. HPD was quantified by applying three different methods (tumor growth rate [TGR], tumor growth kinetics [TGK], and Response Evaluation Criteria in Solid Tumors version 1.1 [RECIST 1.1]). HPD rates were compared between and within both cohorts using the different methods. Results: Using TGR, TGK, and RECIST 1.1, we identified seven (16.7%), seven (16.7%), and six (14.3%) patients with HPD in the nivolumab cohort and three (8.1%), four (10.8%), and five (13.6%) in the docetaxel cohort, respectively. We observed a higher concordance between TGR and TGK (90.1%) compared with RECIST 1.1 (31.3% and 37.5% with TGR and TGK, respectively). We found no significant differences in the overall survival between patients with progressive disease and HPD in either cohort. Conclusions: TGR and TGK revealed high concordance rates for identifying patients with HPD in NSCLC. The incidence of HPD was numerically higher in patients treated with immune checkpoint inhibitors. Standardization of methods for measuring HPD and its exploration in larger studies are needed to establish its clinical meaning in NSCLC

Exploring the association of cancer and depression in electronic health records: combining encoded diagnosis and mining free-text clinical notes

Background: A cancer diagnosis is a source of psychological and emotional stress, which are often maintained for sustained periods of time that may lead to depressive disorders. Depression is one of the most common psychological conditions in patients with cancer. According to the Global Cancer Observatory, breast and colorectal cancers are the most prevalent cancers in both sexes and across all age groups in Spain. Objective: This study aimed to compare the prevalence of depression in patients before and after the diagnosis of breast or colorectal cancer, as well as to assess the usefulness of the analysis of free-text clinical notes in 2 languages (Spanish or Catalan) for detecting depression in combination with encoded diagnoses. Methods: We carried out an analysis of the electronic health records from a general hospital by considering the different sources of clinical information related to depression in patients with breast and colorectal cancer. This analysis included ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) diagnosis codes and unstructured information extracted by mining free-text clinical notes via natural language processing tools based on Systematized Nomenclature of Medicine Clinical Terms that mentions symptoms and drugs used for the treatment of depression. Results: We observed that the percentage of patients diagnosed with depressive disorders significantly increased after cancer diagnosis in the 2 types of cancer considered-breast and colorectal cancers. We managed to identify a higher number of patients with depression by mining free-text clinical notes than the group selected exclusively on ICD-9-CM codes, increasing the number of patients diagnosed with depression by 34.8% (441/1269). In addition, the number of patients with depression who received chemotherapy was higher than those who did not receive this treatment, with significant differences (P<.001). Conclusions: This study provides new clinical evidence of the depression-cancer comorbidity and supports the use of natural language processing for extracting and analyzing free-text clinical notes from electronic health records, contributing to the identification of additional clinical data that complements those provided by coded data to improve the management of these patients.This research was carried out under the framework of the project Creating medically-driven integrative bioinformatics applications focused on oncology, CNS disorders and their comorbidities (MedBioinformatics, H2020-EU; grant 634143); and partially funded by the Institute of Health Carlos III (project IMPaCT-Data; IMP/00019) and cofunded by the European Union, European Regional Development Fund (“A way to make Europe”); and the Clinical Knowledge Aggregation by Mining Medical Reports (CliKA-MinE; PI17/00230), which is funded by Institute of Health Carlos III and cofunded by the European Union

Comprehensive analysis of metabolic isozyme targets in cancer

Metabolic reprogramming is a hallmark of malignant transformation, and loss of isozyme diversity (LID) contributes to this process. Isozymes are distinct proteins that catalyze the same enzymatic reaction but can have different kinetic characteristics, subcellular localization, and tissue specificity. Cancer-dominant isozymes that catalyze rate-limiting reactions in critical metabolic processes represent potential therapeutic targets. Here, we examined the isozyme expression patterns of 1,319 enzymatic reactions in 14 cancer types and their matching normal tissues using The Cancer Genome Atlas mRNA expression data to identify isozymes that become cancer-dominant. Of the reactions analyzed, 357 demonstrated LID in at least one cancer type. Assessment of the expression patterns in over 600 cell lines in the Cancer Cell Line Encyclopedia showed that these reactions reflect cellular changes instead of differences in tissue composition; 50% of the LID-affected isozymes showed cancer-dominant expression in the corresponding cell lines. The functional importance of the cancer-dominant isozymes was assessed in genome-wide CRISPR and RNAi loss-of-function screens: 17% were critical for cell proliferation, indicating their potential as therapeutic targets. Lists of prioritized novel metabolic targets were developed for 14 cancer types; the most broadly shared and functionally validated target was acetyl-CoA carboxylase 1 (ACC1). Small molecule inhibition of ACC reduced breast cancer viability in vitro and suppressed tumor growth in cell line- and patient-derived xenografts in vivo. Evaluation of the effects of drug treatment revealed significant metabolic and transcriptional perturbations. Overall, this systematic analysis of isozyme expression patterns elucidates an important aspect of cancer metabolic plasticity and reveals putative metabolic vulnerabilities