Cluster classification of a Brazilian gastric cancer cohort reveals remarkable populational differences in normal p53 rate.

BACKGROUND: Queiroz et al. showed that the application of cluster methodology for classifying gastric cancer is suitable and efficient within a Brazilian cohort, which is known for its population heterogeneity. The study highlighted the potential utilization of this method within public health services due to its low-cost, presenting a viable means to improve the diagnosis and prognosis of gastric cancer. BACKGROUND: Our Brazilian cohort with gastric cancer has a distinct distribution between mutated and normal p53. BACKGROUND: New genetic marker-based classifications improve gastric cancer diagnosis accuracy. BACKGROUND: Machine learning integration enhances predictive value in gastric cancer diagnosis. BACKGROUND: Molecular biomarkers complement clinical decisions, advancing personalized medicine. OBJECTIVE: Gastric adenocarcinoma remains an aggressive disease with a poor prognosis, as evidenced by a 5-year survival rate of approximately 31%. The histological classifications already proposed do not accurately reflect the high biological heterogeneity of this neoplasm, particularly in diverse populations, and new classification systems using genetic markers have recently been proposed. Following these newly proposed models, we aimed to assess the cluster distribution in a Brazilian cohort. Furthermore, we evaluated whether the inclusion of other clinical and histological parameters could enhance the predictive value. METHODS: We used a previously described four-immunohistochemistry/EBER-ISH marker to classify a cohort of 30 Brazilian patients with gastric adenocarcinoma into five different clusters and compared the distribution with other genetically diverse populations. Furthermore, we used artificial intelligence methods to evaluate whether other clinical and pathological parameters could improve the results of the methodology. RESULTS: Disclosing the genetic variability between populations, we observed a more balanced distribution of the aberrant/normal p53 ratio (0.6) between patients negative for the other markers tested, unlike previous studies with Asian and North American populations. In addition, decision tree analysis reinforced the efficiency of these new classifications, as the stratification accuracy was not altered with or without additional data. CONCLUSION: Our study underscores the importance of local research in characterizing diverse populations and highlights the complementary role of molecular biomarkers in personalized medicine for gastric adenocarcinoma, enhancing diagnostic accuracy and potentially improving survival rates.

RAP1-GTPase immunostaining is altered in human precancerous and cancerous cervical lesions.

Aim: This study investigated RAP1 immunostaining variation in different cell types during CC progression.Methods: Paraffin-embedded cervical tissues from 101 patients were categorized into control, pre-neoplastic and neoplastic groups. RAP1 immunolocalization, HPV detection and genotyping were performed. A semiquantitative immunoreactive score was employed to compare labeling intensity, cellular localization, nuclear labeling, percentage and distribution of reactive cells.Results: 73% (72/99) of cervical specimens were HPV+. RAP1 was localized in the nucleus and cytoplasm of all samples. Cytoplasmic RAP1 immunoscore was higher than nuclear score in all CC groups. RAP1 intensity increased with lesion severity. SCC samples exhibited predominantly intense RAP1 immunostaining.Conclusion: RAP1 is an efficient biomarker for detecting invasive CC lesions but has limited utility in distinguishing SCC grades.

[Box: see text].

Evaluation of Artificial Intelligence-Based Gleason Grading Algorithms "in the Wild".

The biopsy Gleason score is an important prognostic marker for prostate cancer patients. It is, however, subject to substantial variability among pathologists. Artificial intelligence (AI)-based algorithms employing deep learning have shown their ability to match pathologists' performance in assigning Gleason scores, with the potential to enhance pathologists' grading accuracy. The performance of Gleason AI algorithms in research is mostly reported on common benchmark data sets or within public challenges. In contrast, many commercial algorithms are evaluated in clinical studies, for which data are not publicly released. As commercial AI vendors typically do not publish performance on public benchmarks, comparison between research and commercial AI is difficult. The aims of this study are to evaluate and compare the performance of top-ranked public and commercial algorithms using real-world data. We curated a diverse data set of whole-slide prostate biopsy images through crowdsourcing containing images with a range of Gleason scores and from diverse sources. Predictions were obtained from 5 top-ranked public algorithms from the Prostate cANcer graDe Assessment (PANDA) challenge and 2 commercial Gleason grading algorithms. Additionally, 10 pathologists (A.C., C.R., J.v.I., K.R.M.L., P.R., P.G.S., R.G., S.F.K.J., T.v.d.K., X.F.) evaluated the data set in a reader study. Overall, the pairwise quadratic weighted kappa among pathologists ranged from 0.777 to 0.916. Both public and commercial algorithms showed high agreement with pathologists, with quadratic kappa ranging from 0.617 to 0.900. Commercial algorithms performed on par or outperformed top public algorithms.

Linking tumor immune infiltrate and systemic immune mediators to treatment response and prognosis in advanced cervical cancer.

Cervical cancer (CC) poses a significant burden on individuals in developing regions, exhibiting heterogeneous responses to standard chemoradiation therapy, and contributing to substantial mortality rates. Unraveling host immune dynamics holds promise for innovative therapies and discovery of clinically relevant biomarkers. We studied prospectively locally advanced CC patients pre-treatment, stratifying them as responders (R) or non-responders (NR). R patients had increased tumor-infiltrating lymphocytes (TILs), while NR patients showed elevated PD-1 scores, CD8+ and PD-L2+ TILs, and PD-L1 immune reactivity. NR patients exhibited higher systemic soluble mediators correlating with TIL immune markers. R patients demonstrated functional polarization of CD4 T cells (Th1, Th2, Th17, and Treg), while CD8+ T cells and CD68+ macrophages predominated in the NR group. Receiver operating characteristic analysis identified potential CC response predictors, including PD-L1-immunoreactive (IR) area, PD-L2, CD8, FGF-basic, IL-7, IL-8, IL-12p40, IL-15, and TNF-alpha. Dysfunctional TILs and imbalanced immune mediators contribute to therapeutic insufficiency, shedding light on local and systemic immune interplay. Our study informs immunological signatures for treatment prediction and CC prognosis.

EGFR Mutation Detection in Brazilian Patients With Non-Small-Cell Lung Cancer: Lessons From Real-World Data Scenario of Molecular Testing.

PURPOSE: There is a paucity of consistent data concerning genetic mutations in Brazilian patients with lung cancer. The aim of this study was to retrospectively analyze epidermal growth factor receptor (EGFR) mutations detected in a real-world scenario using a large cohort of Brazilian patients with non-small-cell lung cancer (NSCLC). MATERIALS AND METHODS: This was a cross-sectional, observational, descriptive study on the basis of a database of EGFR molecular analysis from tumor samples of patients with a confirmatory histopathological diagnosis of primary lung cancer. Specimens were collected from 2013 to 2017 and were tested using cobas, next-generation sequencing, and Sanger sequencing platforms. RESULTS: A total of 7,413 tumor specimens were tested. The patients were predominantly women with a median age of 67.0 years. Patients with at least one mutation represented 24.2% of the total sample. Among the positive patients, the majority had just one mutation, but two or more simultaneous mutations were observed in 1.52% of patients. Exon 19 deletion was the most prevalent alteration in the sample (12.8%), followed by exon 21 L858R (6.9%) and exon 20 insertion (1.6%). All others were considered uncommon mutations and were observed in 18.5% of all mutated patients and 4.0% of the total sample (2.3%-18.7% depending on the sequencing method). CONCLUSION: This study examined the prevalence of EGFR mutations in Brazilian patients with NSCLC using different technologies, suggesting that the type of method used, directed or nondirected against specific mutations, influences the analysis, particularly for uncommon mutations, which will be missed by mutation-specific approaches such as cobas testing. Our estimates are the largest in Latin America and are consistent with previous reports from other parts of the world. Besides the variability in methods described here as technology incorporation advances in a nonhomogeneous manner, it is probably like the real-world clinical setting Brazilian oncologists face in their daily practice.

Association of human papillomavirus (HPV), p16, p53 and p63 expression with non-bilharzia-associated squamous cell carcinoma of the bladder and algorithm construction for histopathological grading prediction.

OBJECTIVE: To investigate the expression of human papillomavirus (HPV), p16, p53, and p63 in non-schistosomiasis-related squamous cell carcinoma of the bladder and to develop an accurate and automated tool to predict histological classification based on clinicopathological features. METHODS: Twenty-eight patients with primary bladder pure squamous cell carcinoma who underwent cystectomy or transurethral resection of bladder tumor (TURBT) for bladder cancer between January 2011 and July 2017 were evaluated. Clinical data and follow-up information were obtained from medical records. Formalin-fixed, paraffin-embedded surgical specimens were used for immunohistochemical staining for p16, p53, and p63. Human papillomavirus detection was evaluated by PCR. Statistical analysis was performed, and statistical significance was set at p<0.05. Finally, decision trees were built to classify patients' prognostic features. Leave-one-out cross-validation was used to test the generalizability of the model. RESULTS: Neither direct HPV detection nor its indirect marker (p16 protein) was identified in most cases. The absence of p16 was correlated with less aggressive histological grading (p=0.040). The positive p16 staining detection found only in pT1 and pT2 cases in our sample suggests a possible role for this tumor suppressor protein in the initial stages of bladder squamous cell carcinoma. The decision trees constructed described the relationship between clinical features, such as hematuria/dysuria, the level of tumor invasion, HPV status, lymphovascular invasion, gender, age, compromised lymph nodes, and tumor degree differentiation, with high classification accuracy. CONCLUSION: The algorithm classifier approach established decision pathways for semi-automatic tumor histological classification, laying the foundation for tailored semi-automated decision support systems for pathologists.

Association of human papillomavirus (HPV), p16, p53 and p63 expression with non-bilharzia-associated squamous cell carcinoma of the bladder and algorithm construction for histopathological grading prediction

ABSTRACT Objective To investigate the expression of human papillomavirus (HPV), p16, p53, and p63 in non-schistosomiasis-related squamous cell carcinoma of the bladder and to develop an accurate and automated tool to predict histological classification based on clinicopathological features. Methods Twenty-eight patients with primary bladder pure squamous cell carcinoma who underwent cystectomy or transurethral resection of bladder tumor (TURBT) for bladder cancer between January 2011 and July 2017 were evaluated. Clinical data and follow-up information were obtained from medical records. Formalin-fixed, paraffin-embedded surgical specimens were used for immunohistochemical staining for p16, p53, and p63. Human papillomavirus detection was evaluated by PCR. Statistical analysis was performed, and statistical significance was set at p<0.05. Finally, decision trees were built to classify patients' prognostic features. Leave-one-out cross-validation was used to test the generalizability of the model. Results Neither direct HPV detection nor its indirect marker (p16 protein) was identified in most cases. The absence of p16 was correlated with less aggressive histological grading (p=0.040). The positive p16 staining detection found only in pT1 and pT2 cases in our sample suggests a possible role for this tumor suppressor protein in the initial stages of bladder squamous cell carcinoma. The decision trees constructed described the relationship between clinical features, such as hematuria/dysuria, the level of tumor invasion, HPV status, lymphovascular invasion, gender, age, compromised lymph nodes, and tumor degree differentiation, with high classification accuracy. Conclusion The algorithm classifier approach established decision pathways for semi-automatic tumor histological classification, laying the foundation for tailored semi-automated decision support systems for pathologists.

Barriers in precision medicine implementation among Advanced Nonsquamous Cell Lung Cancer-patients: A Real-World Evidence Scenario.

Background: Precision oncology has a prominent role in nonsquamous non-small cell lung cancer (nsNSCLC) treatment progress; however, its access in a real-world scenario might be limited. Objective: To investigate the time spent in nsNSCLC molecular profile evaluation and its influence on clinical decisions. Methods: nsNSCLC patients who underwent molecular testing in a private referral Brazilian center between November 2015 and February 2020 were identified. The interval from nsNSCLC diagnosis to the characterization of the molecular profile was determined. Other outcomes, focusing on the biomarker tissue journey, were also assessed. Results: In this cohort (n = 78), the median time between the advanced nsNSCLC diagnosis and biomarker characterization was 40.5 days (range, 29.5-68.5). The median interval between the diagnosis and the test request was longer than the interval between the request and the results (respectively 29.0 versus 12.0 days; p < 0.001). At the treatment initiation, 51% (36/71) of the patients who received any systemic therapy did not have their driver mutations panel results available. But on these, 42% (15/36) had a targetable alteration identified later on. Among patients harboring a targetable alteration, only 46% (n = 13/28) received a tyrosine kinase inhibitor (TKI) as first-line therapy. The median time to the TKI initiation was even longer than the median time to all treatment initiation (92.0 versus 40.0 days). Conclusions: Our data show a long median time from advanced nsNSCLC diagnosis and the availability of the biomarker testing in medical practice, which impacted the choice of a non-personalized therapy as the first-line.

O que dizem as informações sobre mortalidade dos Registros Hospitalares de Câncer (RHC) em hospital de referência de Minas Gerais, 2016-2017 / What the information on mortality from the Hospital Cancer Registry (RHC) reveals about a reference hospital in Minas Gerais, 2016-2017

Resumo Introdução A qualidade das informações dos Registros Hospitalares de Câncer (RHC) necessita de avaliação quanto à cobertura, completitude e concordância da causa básica(CB) com o Sistema de Informações sobre Mortalidade (SIM). Objetivo Avaliar a qualidade dos RHC nas duas unidades hospitalares do Instituto Mário Penna: Hospitais Mário Penna (HMP) e Luxemburgo (HL), Belo Horizonte, Minas Gerais, em 2016 e 2017, nos atributos mencionados. Método Por captura-recaptura (RHC x RHC), avaliaram-se, por unidade, cobertura, completitude da variável "óbito por câncer" e concordância da a (CB) com a causa da pesquisa (CP). Por relacionamento determinístico (RHC x SIM) avaliaram-se cobertura e concordância da CB. Resultados A cobertura dos RHC foi boa eexcelente (88,8% e 95,3%); a completitude foi ruim (34,6% e 32,6%) no HMP e HL respectivamente; por capítulo da CID-10, não houve concordância da CB com a CP. Observaram-se excelentes cobertura (94,7%) e concordância (94,5%) entre CP e SIM; observou-se sub-registro de 38 neoplasias no SIM, com reclassificação de causas pouco úteis. Conclusão A aplicação das técnicas de captura-recaptura e relacionamento determinístico contribuiu para a melhora da qualidade da informação dos RHC, com redução da incompletude nos RHC e correção da CB nos RHC e no SIM.

Abstract Bakground The quality of information from the Hospital Cancer Records (HRC) needs to be evaluated regarding coverage, completeness and agreement between the underlying cause (UC) as registered in the HRC and the Mortality Information System (SIM). Objective To assess the quality of the HRC in the two Instituto Mário Penna hospitals: Mário Penna (HMP) and Luxemburgo (HL) in Belo Horizonte, Minas Gerais, between 2016-2017. Method By capture-recapture (RHC x RHC), we assessed coverage, completeness of the "cancer death" variable and agreement between underlying cause (UC) with the cause of the research (CR), in each hospital. Deterministic relationship (RHC x SIM) was used to asses UC coverage and agreement between systems. Results The coverage of deaths at the HRC was good/excellent (88.8% and 95.3%); completeness was poor (34.6% and 32.6%) in HMP and HL respectively; per ICD-10 chapter, there was no agreement between CB and CP. Excellent coverage (94.7%) and agreement (94.5%) of CR and SIM were observed; 38 neoplasms were under-reported in the SIM, with reclassification of less useful causes. Conclusion Applying capture-recapture and deterministic linkage techniques contributed in improving the quality of information in the HRC, with a reduction in incompleteness in the HRC and correction of the UC in both HRC and SIM.

Cervical Cancer Stem-Like Cell Transcriptome Profiles Predict Response to Chemoradiotherapy.

Cervical cancer (CC) represents a major global health issue, particularly impacting women from resource constrained regions worldwide. Treatment refractoriness to standard chemoradiotheraphy has identified cancer stem cells as critical coordinators behind the biological mechanisms of resistance, contributing to CC recurrence. In this work, we evaluated differential gene expression in cervical cancer stem-like cells (CCSC) as biomarkers related to intrinsic chemoradioresistance in CC. A total of 31 patients with locally advanced CC and referred to Mário Penna Institute (Belo Horizonte, Brazil) from August 2017 to May 2018 were recruited for the study. Fluorescence-activated cell sorting was used to enrich CD34+/CD45- CCSC from tumor biopsies. Transcriptome was performed using ultra-low input RNA sequencing and differentially expressed genes (DEGs) using Log2 fold differences and adjusted p-value < 0.05 were determined. The analysis returned 1050 DEGs when comparing the Non-Responder (NR) (n=10) and Responder (R) (n=21) groups to chemoradiotherapy. These included a wide-ranging pattern of underexpressed coding genes in the NR vs. R patients and a panel of lncRNAs and miRNAs with implications for CC tumorigenesis. A panel of biomarkers was selected using the rank-based AUC (Area Under the ROC Curve) and pAUC (partial AUC) measurements for diagnostic sensitivity and specificity. Genes overlapping between the 21 highest AUC and pAUC loci revealed seven genes with a strong capacity for identifying NR vs. R patients (ILF2, RBM22P2, ACO16722.1, AL360175.1 and AC092354.1), of which four also returned significant survival Hazard Ratios. This study identifies DEG signatures that provide potential biomarkers in CC prognosis and treatment outcome, as well as identifies potential alternative targets for cancer therapy.

Independent real-world application of a clinical-grade automated prostate cancer detection system.

Artificial intelligence (AI)-based systems applied to histopathology whole-slide images have the potential to improve patient care through mitigation of challenges posed by diagnostic variability, histopathology caseload, and shortage of pathologists. We sought to define the performance of an AI-based automated prostate cancer detection system, Paige Prostate, when applied to independent real-world data. The algorithm was employed to classify slides into two categories: benign (no further review needed) or suspicious (additional histologic and/or immunohistochemical analysis required). We assessed the sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs) of a local pathologist, two central pathologists, and Paige Prostate in the diagnosis of 600 transrectal ultrasound-guided prostate needle core biopsy regions ('part-specimens') from 100 consecutive patients, and to ascertain the impact of Paige Prostate on diagnostic accuracy and efficiency. Paige Prostate displayed high sensitivity (0.99; CI 0.96-1.0), NPV (1.0; CI 0.98-1.0), and specificity (0.93; CI 0.90-0.96) at the part-specimen level. At the patient level, Paige Prostate displayed optimal sensitivity (1.0; CI 0.93-1.0) and NPV (1.0; CI 0.91-1.0) at a specificity of 0.78 (CI 0.64-0.89). The 27 part-specimens considered by Paige Prostate as suspicious, whose final diagnosis was benign, were found to comprise atrophy (n = 14), atrophy and apical prostate tissue (n = 1), apical/benign prostate tissue (n = 9), adenosis (n = 2), and post-atrophic hyperplasia (n = 1). Paige Prostate resulted in the identification of four additional patients whose diagnoses were upgraded from benign/suspicious to malignant. Additionally, this AI-based test provided an estimated 65.5% reduction of the diagnostic time for the material analyzed. Given its optimal sensitivity and NPV, Paige Prostate has the potential to be employed for the automated identification of patients whose histologic slides could forgo full histopathologic review. In addition to providing incremental improvements in diagnostic accuracy and efficiency, this AI-based system identified patients whose prostate cancers were not initially diagnosed by three experienced histopathologists. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

A fertility-oriented method for histological processing of testicular biopsies in men with azoospermia.

The present study was designed to evaluate whether tissue preparation by glutaraldehyde and glycol methacrylate (G/GMA) improves the diagnostic assessment of testicular biopsies from azoospermic men when compared to the standard tissue preparation using Bouin's solution and paraffin. We prospectively included a total of 21 testicular biopsies of sexually mature men aged 29-50 years with infertility and azoospermia. One testicular biopsy fragment from each patient was processed by the G/GMA method, whereas another tissue fragment was contemporarily processed by the conventional Bouin/paraffin (B/P) method. The G/GMA method provided better resolution of cytological details of the seminiferous epithelium, changing the final diagnosis in four cases. The medians of Bergmann's spermatogenesis scores were 0.25 (interquartile range 0.04-0.88) for B/P preparations and 0.79 (interquartile range 0.17-0.96) for G/GMA preparations. Both techniques allowed accurate prediction of sperm recovery from the biopsies (B/P, area under the receiver operating characteristics [ROC] curve 0.88, 95% confidence interval [CI] 0.75-1.00; G/GMA, area under the ROC curve 0.94, 95% CI 0.86-1.00). We conclude that human testicular biopsy preparation with G/GMA improved image resolution under light microscopy and produced more reliable results for the evaluation of spermatogenesis in comparison with B/P, allowing a more precise fertility-oriented diagnosis in azoospermic men.Abbreviations: B/P: Bouin/paraffin; GMA: glycol methacrylate; G/GMA: glutaraldehyde and glycol methacrylate; ICSI: intracytoplasmic sperm injection; OA: obstructive azoospermia; NOA: nonobstructive azoospermia; TESE: testicular sperm extraction.

Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists.

The Gleason score is the most important prognostic marker for prostate cancer patients, but it suffers from significant observer variability. Artificial intelligence (AI) systems based on deep learning can achieve pathologist-level performance at Gleason grading. However, the performance of such systems can degrade in the presence of artifacts, foreign tissue, or other anomalies. Pathologists integrating their expertise with feedback from an AI system could result in a synergy that outperforms both the individual pathologist and the system. Despite the hype around AI assistance, existing literature on this topic within the pathology domain is limited. We investigated the value of AI assistance for grading prostate biopsies. A panel of 14 observers graded 160 biopsies with and without AI assistance. Using AI, the agreement of the panel with an expert reference standard increased significantly (quadratically weighted Cohen's kappa, 0.799 vs. 0.872; p = 0.019). On an external validation set of 87 cases, the panel showed a significant increase in agreement with a panel of international experts in prostate pathology (quadratically weighted Cohen's kappa, 0.733 vs. 0.786; p = 0.003). In both experiments, on a group-level, AI-assisted pathologists outperformed the unassisted pathologists and the standalone AI system. Our results show the potential of AI systems for Gleason grading, but more importantly, show the benefits of pathologist-AI synergy.

Real-World Molecular Testing and Treatment Patterns in Brazilian Patients with Newly Diagnosed Locally Advanced or Metastatic NSCLC.

OBJECTIVES: To evaluate the molecular testing and treatment patterns in a retrospective cohort of newly diagnosed treatment-naïve patients with locally advanced or metastatic non-small-cell lung cancer (NSCLC). METHODS: This is an observational retrospective cohort study conducted across 10 cancer centers in Brazil. Treatment-naïve patients with locally advanced or metastatic NSCLC were enrolled from January to December 2014. The following data were collected from the medical records of patients from diagnosis until the last record (death, loss to follow-up, or the end of the maximum follow-up period): demographics; medical history; smoking status; disease characteristics; previous treatments; and molecular testing patterns and results. The overall survival (OS) was also estimated. RESULTS: A total of 391 patients from 8 different Brazilian states were included, with a median age of 64.1 years (23.7-98.7), with most patients being males (60.1%). The smoking status of 74.2% of patients was a 'former' or 'current smoker'. Stage IV NSCLC at diagnosis was observed in 82.4% of patients, with 269 of them (68.8%) presenting adenocarcinoma (ADC). Among the stage IV ADC patients, 54.0% were referred for molecular testing. Among the patients with an available epidermal growth factor receptor (EGFR) mutation status, 31 (24.0%) were EGFR-positive. The first-line treatment was a platinum-based chemotherapy for 98 patients (25.1%), while non-platinum-based regimens were used in 54 patients (13.8%). OS data were available for 370 patients, with a median OS of 10.8 months. Never smokers had a significantly higher median OS versus current or former smokers (14.6 versus 9.1 months; log-rank p=0.003). Among the patients for whom molecular testing data were available, those with EGFR-positive results had a longer median OS (34.6 versus 12.8 months; log-rank p=0.003). CONCLUSION: Our findings provide relevant information for prescribers and policy decision-makers by highlighting the unmet needs of patients and the importance of molecular testing in newly diagnosed locally advanced or metastatic lung adenocarcinoma. We also highlight the respective EGFR-tyrosine kinase inhibitor treatment when the result is positive and the areas in which further efforts are required to grant access to effective treatment.

Real-world molecular testing and treatment patterns in brazilian patients with newly diagnosed locally advanced or metastatic NSCLC

OBJECTIVES: To evaluate the molecular testing and treatment patterns in a retrospective cohort of newly diagnosed treatment-naïve patients with locally advanced or metastatic non-small-cell lung cancer (NSCLC). METHODS: This is an observational retrospective cohort study conducted across 10 cancer centers in Brazil. Treatment-naïve patients with locally advanced or metastatic NSCLC were enrolled from January to December 2014. The following data were collected from the medical records of patients from diagnosis until the last record (death, loss to follow-up, or the end of the maximum follow-up period): demographics; medical history; smoking status; disease characteristics; previous treatments; and molecular testing patterns and results. The overall survival (OS) was also estimated. Results: A total of 391 patients from 8 different Brazilian states were included, with a median age of 64.1 years (23.7-98.7), with most patients being males (60.1%). The smoking status of 74.2% of patients was a 'former' or 'current smoker'. Stage IV NSCLC at diagnosis was observed in 82.4% of patients, with 269 of them (68.8%) presenting adenocarcinoma (ADC). Among the stage IV ADC patients, 54.0% were referred for molecular testing. Among the patients with an available epidermal growth factor receptor (EGFR) mutation status, 31 (24.0%) were EGFR-positive. The first-line treatment was a platinum-based chemotherapy for 98 patients (25.1%), while non-platinum-based regimens were used in 54 patients (13.8%). OS data were available for 370 patients, with a median OS of 10.8 months. Never smokers had a significantly higher median OS versus current or former smokers (14.6 versus 9.1 months; log-rank p=0.003). Among the patients for whom molecular testing data were available, those with EGFR-positive results had a longer median OS (34.6 versus 12.8 months; log-rank p=0.003). Conclusion: Our findings provide relevant information for prescribers and policy decision-makers by highlighting the unmet needs of patients and the importance of molecular testing in newly diagnosed locally advanced or metastatic lung adenocarcinoma. We also highlight the respective EGFR-tyrosine kinase inhibitor treatment when the result is positive and the areas in which further efforts are required to grant access to effective treatment.

Prognostic value of PD-L1 expression for surgically treated localized renal cell carcinoma: implications for risk stratification and adjuvant therapies.

BACKGROUND: We aimed to evaluate the prognostic role of programmed-death receptor ligand (PD-L1) in a multinational cohort of patients with localized renal cell carcinoma (RCC). METHODS: Formalin-fixed paraffin-embedded blocks of 1017 patients from the Latin American Renal Cancer Group were analyzed. Tissue microarrays were immunostained for PD-L1 using a commercially available monoclonal antibody. Expression of PD-L1 in ⩾5% tumor cells was considered positive. PD-1 expression in immune cells was also assessed. All cases were reviewed twice based on antibody expression and compared with a positive control. Cox proportional hazard regression models were used to identify predictors of recurrence-free survival (RFS) and overall survival (OS). RESULTS: A total of 738 cases with complete follow up met criteria. Median age was 57 [interquartile range (IQR): 49-64] years, and median follow up was 34 (IQR: 15-62.9) months. Median tumor size was 5 cm (IQR: 3.0-7.5 cm). Approximately 8.2% and 7.6% of tumors were PD-L1 and programmed cell-death 1 (PD-1) positive, respectively. PD-L1 and PD-1 positivity were significantly associated with higher tumor stage (both p < 0.001), and presence of tumor necrosis and lymphovascular multivariable analyses; PD-L1 positivity was found as a predictor of worse RFS [hazard ratio (HR) = 2.08, p = 0.05] and OS (HR = 2.61, p = 0.02). CONCLUSIONS: PD-L1 positivity was significantly associated with worse outcomes for patients with localized RCC at intermediate follow up. This marker may help stratify patients for stricter surveillance after surgical treatment and provide a basis for checkpoint-inhibitor therapy in the adjuvant setting.

Cervical cancer patients that respond to chemoradiation therapy display an intense tumor infiltrating immune profile before treatment.

Cervical cancer (CC) is a major cause of death and suffering to women globally with 570,000 new cases in 2017. It disproportionately affects those living in resource-constrained countries such as Brazil, with 90% of the deaths from CC happening in low and middle-income countries. Early detection is still the best strategy for improving response to therapy and survival and cases detected in advanced stages show variable response rates to the standard chemoradiation therapy protocols. Both the genetic landscape and the immune status of patients can dramatically affect cancer progression and response to therapy, as well as disease recurrence. Here we performed a comprehensive sequencing analysis using the cancer gene panel - Ion AmpliSeq™ Cancer hotspot Panel V2 CHPv2, as well as determined the immune infiltrate composition of a group of locally advanced CC patients with the goal of identifying genetic and immune characteristics associated with a clinical response to therapy. The expression levels of CD68+ tumor-associated macrophages (TAMs) and CD8+ tumor-infiltrating lymphocytes (TILs), as well as the immune checkpoint molecules PD-1, PD-L1 and PD-L2 in stroma and in tumor regions were analyzed by immunohistochemistry (IHC). The HPV infection status with high-risk strains was also determined. Twenty-one samples from patients with squamous cell carcinoma segregated into responder (11) and non-responder (10) groups according to standard chemoradiation therapy response were studied. Our findings indicate that responder patients showed an increase of an inflammatory tumor microenvironment as indicated by higher numbers of CD8+ and PD-L2+ TILs, as well as higher expression of PD-L1 immunoreactive area, as compared to the non-responder group. Additionally, our results demonstrate a correlation between the number of gene mutations and PD-L2+ TILs in the responder group. The genes PIK3CA and KDR/VEGFR were the most mutated genes, corroborating past findings. Together, these findings indicate an inflammatory tumor microenvironment present in patients that will respond to future chemoradiation treatment as compared to those that will not. This points to possible future predictors of response to therapy in CC patients.

18F-FDG PET/CT as a prognostic factor in penile cancer.

PURPOSE: Penile cancer (PC) is a rare neoplasm with an aggressive behavior and variable prognosis. Lymph node (LN) involvement and pathological features of the primary lesion have been proven to be the most important survival factors. Positron emission tomography/computed tomography with fluorodeoxyglucose labelled with fluorine-18 (18F-FDG PET/CT) provides information on tumor staging and works as a prognostic factor, with promising results in other carcinomas. The aim of the present study is to evaluate PET/CT as a prognostic factor in PC. METHODS: Fifty-five patients (mean age 56.6 y) diagnosed with penile squamous cell carcinoma were prospectively evaluated from 2012 to 2014. All subjects underwent 18F-FDG PET/CT before treatment and were regularly followed after surgery. RESULTS: Out of the 53 patients selected, 17 (32.1%) had localized disease (cT1-2) and 24 (45.3%) had palpable nodes (cN+). Partial penile amputation was performed in 38 patients (71.7%) and inguinal lymphadenectomy (LND) in 30 (56.6%). From the LND group, 16 (53.3%) presented with positive neoplastic cells (pN+). Patients with more aggressive disease had a significantly (p = 0.019) higher 18F-FDG tumor uptake (pSUVmax), while inguinal LN uptake (nSUVmax) was able to recognize metastatic LN (p = 0.039). Some pathological prognostic features, when presented, have shown significant changes in pSUVmax values. Receiver operating characteristic (ROC) curves were performed and specific cutoff values of pSUVmax were evaluated to determine sensitivity and specificity. Regarding regional LNs, PET/CT presented a 76.2% accuracy in cN+ patients. After a 39-month follow up, pSUVmax of 16.6 (p = 0.0001) and nSUVmax of 6.5 (p = 0.019) were established as the ideal values to predict cancer-specific survival. The multivariate analysis confirmed nSUVmax as a predictor for LN metastasis (p = 0.043) and pSUVmax as a mean to estimate survival rate (p = 0.05). CONCLUSION: This study showed promising results on the use of 18F-FDG PET/CT as a prognostic tool for PC, using specific cutoff values of pSUVmax and nSUVmax.