METTL13 Methylation of eEF1A Increases Translational Output to Promote Tumorigenesis.

Increased protein synthesis plays an etiologic role in diverse cancers. Here, we demonstrate that METTL13 (methyltransferase-like 13) dimethylation of eEF1A (eukaryotic elongation factor 1A) lysine 55 (eEF1AK55me2) is utilized by Ras-driven cancers to increase translational output and promote tumorigenesis in vivo. METTL13-catalyzed eEF1A methylation increases eEF1A's intrinsic GTPase activity in vitro and protein production in cells. METTL13 and eEF1AK55me2 levels are upregulated in cancer and negatively correlate with pancreatic and lung cancer patient survival. METTL13 deletion and eEF1AK55me2 loss dramatically reduce Ras-driven neoplastic growth in mouse models and in patient-derived xenografts (PDXs) from primary pancreatic and lung tumors. Finally, METTL13 depletion renders PDX tumors hypersensitive to drugs that target growth-signaling pathways. Together, our work uncovers a mechanism by which lethal cancers become dependent on the METTL13-eEF1AK55me2 axis to meet their elevated protein synthesis requirement and suggests that METTL13 inhibition may constitute a targetable vulnerability of tumors driven by aberrant Ras signaling.

Impact of Region-of-Interest Size on Immune Profiling Using Multiplex Immunofluorescence Tyramide Signal Amplification for Paraffin-Embedded Tumor Tissues.

INTRODUCTION: Representative regions of interest (ROIs) analysis from the whole slide images (WSI) are currently being used to study immune markers by multiplex immunofluorescence (mIF) and single immunohistochemistry (IHC). However, the amount of area needed to be analyzed to be representative of the entire tumor in a WSI has not been defined. METHODS: We labeled tumor-associated immune cells by mIF and single IHC in separate cohorts of non-small cell lung cancer (NSCLC) samples and we analyzed them as whole tumor area as well as using different number of ROIs to know how much area will be need to represent the entire tumor area. RESULTS: For mIF using the InForm software and ROI of 0.33 mm2 each, we observed that the cell density data from five randomly selected ROIs is enough to achieve, in 90% of our samples, more than 0.9 of Spearman correlation coefficient and for single IHC using ScanScope tool box from Aperio and ROIs of 1 mm2 each, we found that the correlation value of more than 0.9 was achieved using 5 ROIs in a similar cohort. Additionally, we also observed that each cell phenotype in mIF influence differently the correlation between the areas analyzed by the ROIs and the WSI. Tumor tissue with high intratumor epithelial and immune cells phenotype, quality, and spatial distribution heterogeneity need more area analyzed to represent better the whole tumor area. CONCLUSION: We found that at minimum 1.65 mm2 area is enough to represent the entire tumor areas in most of our NSCLC samples using mIF.

Cellular location and expression of Na+, K+ -ATPase α subunits affect the anti-proliferative activity of oleandrin.

The purpose of this study was to investigate whether intracellular distribution of Na(+), K(+) -ATPase α3 subunit, a receptor for cardiac glycosides including oleandrin, is differentially altered in cancer versus normal cells and whether this altered distribution can be therapeutically targeted to inhibit cancer cell survival. The cellular distribution of Na(+), K(+) -ATPase α3 isoform was investigated in paired normal and cancerous mucosa biopsy samples from patients with lung and colorectal cancers by immunohistochemical staining. The effects of oleandrin on α3 subunit intracellular distribution, cell death, proliferation, and EKR phosphorylation were examined in differentiated and undifferentiated human colon cancer CaCO-2 cells. While Na(+), K(+) -ATPase α3 isoform was predominantly located near the cytoplasmic membrane in normal human colon and lung epithelia, the expression of this subunit in their paired cancer epithelia was shifted to a peri-nuclear position in both a qualitative and quantitative manner. Similarly, distribution of α3 isoform was also shifted from a cytoplasmic membrane location in differentiated human colon cancer CaCO-2 cells to a peri-nuclear position in undifferentiated CaCO-2 cells. Intriguingly, oleandrin exerted threefold stronger anti-proliferative activity in undifferentiated CaCO-2 cells (IC50, 8.25 nM) than in differentiated CaCO-2 cells (IC50, >25 nM). Oleandrin (10 to 20 nM) caused an autophagic cell death and altered ERK phosphorylation in undifferentiated but not in differentiated CaCO-2 cells. These data demonstrate that the intracellular location of Na(+), K(+) -ATPase α3 isoform is altered in human cancer versus normal cells. These changes in α3 cellular location and abundance may indicate a potential target of opportunity for cancer therapy.

Association between Helicobacter pylori infection, mismatch repair, HER2 and tumor-infiltrating lymphocytes in gastric cancer.

BACKGROUND: The influence of Helicobacter-pylori (H. pylori) infection and the characteristics of gastric cancer (GC) on tumor-infiltrating lymphocyte (TIL) levels has not been extensively studied. Analysis of infiltrating-immune-cell subtypes as well as survival is necessary to obtain comprehensive information. AIM: To determine the rates of deficient mismatch-repair (dMMR), HER2-status and H. pylori infection and their association with TIL levels in GC. METHODS: Samples from 503 resected GC tumors were included and TIL levels were evaluated following the international-TILs-working-group recommendations with assessment of the intratumoral (IT), stromal (ST) and invasive-border (IB) compartments. The density of CD3, CD8 and CD163 immune cells, and dMMR and HER2-status were determined by immunohistochemistry (IHC). H. pylori infection was evaluated by routine histology and quantitative PCR (qPCR) in a subset of samples. RESULTS: dMMR was found in 34.4%, HER2+ in 5% and H. pylori-positive in 55.7% of samples. High IT-TIL was associated with grade-3 (P = 0.038), while ST-TIL with grade-1 (P < 0.001), intestinal-histology (P < 0.001) and no-recurrence (P = 0.003). dMMR was associated with high TIL levels in the ST (P = 0.019) and IB (P = 0.01) compartments, and ST-CD3 (P = 0.049) and ST-CD8 (P = 0.05) densities. HER2- was associated with high IT-CD8 (P = 0.009). H. pylori-negative was associated with high IT-TIL levels (P = 0.009) when assessed by routine-histology, and with high TIL levels in the 3 compartments (P = 0.002-0.047) and CD8 density in the IT and ST compartments (P = 0.001) when assessed by qPCR. A longer overall survival was associated with low IT-CD163 (P = 0.003) and CD8/CD3 (P = 0.001 in IT and P = 0.002 in ST) and high IT-CD3 (P = 0.021), ST-CD3 (P = 0.003) and CD3/CD163 (P = 0.002). CONCLUSION: TIL levels were related to dMMR and H. pylori-negativity. Low CD8/CD3 and high CD163/CD3 were associated with lower recurrence and longer survival.

Immune cellular patterns of distribution affect outcomes of patients with non-small cell lung cancer.

Studying the cellular geographic distribution in non-small cell lung cancer is essential to understand the roles of cell populations in this type of tumor. In this study, we characterize the spatial cellular distribution of immune cell populations using 23 makers placed in five multiplex immunofluorescence panels and their associations with clinicopathologic variables and outcomes. Our results demonstrate two cellular distribution patterns-an unmixed pattern mostly related to immunoprotective cells and a mixed pattern mostly related to immunosuppressive cells. Distance analysis shows that T-cells expressing immune checkpoints are closer to malignant cells than other cells. Combining the cellular distribution patterns with cellular distances, we can identify four groups related to inflamed and not-inflamed tumors. Cellular distribution patterns and distance are associated with survival in univariate and multivariable analyses. Spatial distribution is a tool to better understand the tumor microenvironment, predict outcomes, and may can help select therapeutic interventions.

Pathological Response and Immune Biomarker Assessment in Non-Small-Cell Lung Carcinoma Receiving Neoadjuvant Immune Checkpoint Inhibitors.

Lung cancer is the leading cause of cancer incidence and mortality worldwide. Adjuvant and neoadjuvant chemotherapy have been used in the perioperative setting of non-small-cell carcinoma (NSCLC); however, the five-year survival rate only improves by about 5%. Neoadjuvant treatment with immune checkpoint inhibitors (ICIs) has become significant due to improved survival in advanced NSCLC patients treated with immunotherapy agents. The assessment of pathology response has been proposed as a surrogate indicator of the benefits of neaodjuvant therapy. An outline of recommendations has been published by the International Association for the Study of Lung Cancer (IASLC) for the evaluation of pathologic response (PR). However, recent studies indicate that evaluations of immune-related changes are distinct in surgical resected samples from patients treated with immunotherapy. Several clinical trials of neoadjuvant immunotherapy in resectable NSCLC have included the study of biomarkers that can predict the response of therapy and monitor the response to treatment. In this review, we provide relevant information on the current recommendations of the assessment of pathological responses in surgical resected NSCLC tumors treated with neoadjuvant immunotherapy, and we describe current and potential biomarkers to predict the benefits of neoadjuvant immunotherapy in patients with resectable NSCLC.

Immuno-profiling and cellular spatial analysis using five immune oncology multiplex immunofluorescence panels for paraffin tumor tissue.

Multiplex immunofluorescence (mIF) has arisen as an important tool for immuno-profiling tumor tissues. We updated our manual protocol into an automated protocol that allows the use of up to seven markers in five mIF panels to apply to formalin-fixed paraffin-embedded tumor tissues. Using a tyramide signal amplification system, we optimized five mIF panels that included cytokeratin to characterize malignant cells (MCs), immune checkpoint markers (i.e., PD-L1, B7-H3, B7-H4, IDO-1, VISTA, LAG3, ICOS, TIM3, and OX40), tumor-infiltrating lymphocytic markers (i.e., CD3, CD8, CD45RO, granzyme B, PD-1, and FOXP3), and markers to characterize myeloid-derived suppressor cells (i.e., CD68, CD66b, CD14, CD33, Arg-1, and CD11b). To determine analytical reproducibility and the impact of those panels for immuno-profiling tumor tissues, we performed an exploratory analysis in a set of non-small cell lung cancer (NSCLC) samples. The slides were scanned, and the different cell phenotypes were quantified by simultaneous co-localizations with the markers using image analysis software. Comparison between the time points of staining showed high analytical reproducibility. The analysis of NSCLC cases showed an immunosuppressive microenvironment with PD-L1/PD-1 expression as a predominant axis. Interestingly, high density of MCs expressing B7-H4 was correlated with recurrence. Unexpectedly, MCs expressing OX40 were also detected, and those cells were a closer distance to CD3+T-cells than were MCs expressing other immune checkpoints. Two different cellular patterns of spatial distribution were determined according the CD3 distribution, and the predominant pattern was related with active immunosuppressive interaction with MCs. Our study shows that these five mIF panels can identify multiple targets in a single cell with high reproducibility. The study of different cell populations and their spatial relationship can open new ideas for therapeutic approaches.

Cross-Site Concordance Evaluation of Tumor DNA and RNA Sequencing Platforms for the CIMAC-CIDC Network.

PURPOSE: Whole-exome (WES) and RNA sequencing (RNA-seq) are key components of cancer immunogenomic analyses. To evaluate the consistency of tumor WES and RNA-seq profiling platforms across different centers, the Cancer Immune Monitoring and Analysis Centers (CIMAC) and the Cancer Immunologic Data Commons (CIDC) conducted a systematic harmonization study. EXPERIMENTAL DESIGN: DNA and RNA were centrally extracted from fresh frozen and formalin-fixed paraffin-embedded non-small cell lung carcinoma tumors and distributed to three centers for WES and RNA-seq profiling. In addition, two 10-plex HapMap cell line pools with known mutations were used to evaluate the accuracy of the WES platforms. RESULTS: The WES platforms achieved high precision (> 0.98) and recall (> 0.87) on the HapMap pools when evaluated on loci using > 50× common coverage. Nonsynonymous mutations clustered by tumor sample, achieving an index of specific agreement above 0.67 among replicates, centers, and sample processing. A DV200 > 24% for RNA, as a putative presequencing RNA quality control (QC) metric, was found to be a reliable threshold for generating consistent expression readouts in RNA-seq and NanoString data. MedTIN > 30 was likewise assessed as a reliable RNA-seq QC metric, above which samples from the same tumor across replicates, centers, and sample processing runs could be robustly clustered and HLA typing, immune infiltration, and immune repertoire inference could be performed. CONCLUSIONS: The CIMAC collaborating laboratory platforms effectively generated consistent WES and RNA-seq data and enable robust cross-trial comparisons and meta-analyses of highly complex immuno-oncology biomarker data across the NCI CIMAC-CIDC Network.

State-of-the-Art of Profiling Immune Contexture in the Era of Multiplexed Staining and Digital Analysis to Study Paraffin Tumor Tissues.

Multiplexed platforms for multiple epitope detection have emerged in the last years as very powerful tools to study tumor tissues. These revolutionary technologies provide important visual techniques for tumor examination in formalin-fixed paraffin-embedded specimens to improve the understanding of the tumor microenvironment, promote new treatment discoveries, aid in cancer prevention, as well as allowing translational studies to be carried out. The aim of this review is to highlight the more recent methodologies that use multiplexed staining to study simultaneous protein identification in formalin-fixed paraffin-embedded tumor tissues for immune profiling, clinical research, and potential translational analysis. New multiplexed methodologies, which permit the identification of several proteins at the same time in one single tissue section, have been developed in recent years with the ability to study different cell populations, cells by cells, and their spatial distribution in different tumor specimens including whole sections, core needle biopsies, and tissue microarrays. Multiplexed technologies associated with image analysis software can be performed with a high-quality throughput assay to study cancer specimens and are important tools for new discoveries. The different multiplexed technologies described in this review have shown their utility in the study of cancer tissues and their advantages for translational research studies and application in cancer prevention and treatments.

Development and Validation of a Pathology Image Analysis-based Predictive Model for Lung Adenocarcinoma Prognosis - A Multi-cohort Study.

Prediction of disease prognosis is essential for improving cancer patient care. Previously, we have demonstrated the feasibility of using quantitative morphological features of tumor pathology images to predict the prognosis of lung cancer patients in a single cohort. In this study, we developed and validated a pathology image-based predictive model for the prognosis of lung adenocarcinoma (ADC) patients across multiple independent cohorts. Using quantitative pathology image analysis, we extracted morphological features from H&E stained sections of formalin fixed paraffin embedded (FFPE) tumor tissues. A prediction model for patient prognosis was developed using tumor tissue pathology images from a cohort of 91 stage I lung ADC patients from the Chinese Academy of Medical Sciences (CAMS), and validated in ADC patients from the National Lung Screening Trial (NLST), and the UT Special Program of Research Excellence (SPORE) cohort. The morphological features that are associated with patient survival in the training dataset from the CAMS cohort were used to develop a prognostic model, which was independently validated in both the NLST (n = 185) and the SPORE (n = 111) cohorts. The association between predicted risk and overall survival was significant for both the NLST (Hazard Ratio (HR) = 2.20, pv = 0.01) and the SPORE cohorts (HR = 2.15 and pv = 0.044), respectively, after adjusting for key clinical variables. Furthermore, the model also predicted the prognosis of patients with stage I ADC in both the NLST (n = 123, pv = 0.0089) and SPORE (n = 68, pv = 0.032) cohorts. The results indicate that the pathology image-based model predicts the prognosis of ADC patients across independent cohorts.

Artificial Intelligence in Lung Cancer Pathology Image Analysis.

OBJECTIVE: Accurate diagnosis and prognosis are essential in lung cancer treatment selection and planning. With the rapid advance of medical imaging technology, whole slide imaging (WSI) in pathology is becoming a routine clinical procedure. An interplay of needs and challenges exists for computer-aided diagnosis based on accurate and efficient analysis of pathology images. Recently, artificial intelligence, especially deep learning, has shown great potential in pathology image analysis tasks such as tumor region identification, prognosis prediction, tumor microenvironment characterization, and metastasis detection. MATERIALS AND METHODS: In this review, we aim to provide an overview of current and potential applications for AI methods in pathology image analysis, with an emphasis on lung cancer. RESULTS: We outlined the current challenges and opportunities in lung cancer pathology image analysis, discussed the recent deep learning developments that could potentially impact digital pathology in lung cancer, and summarized the existing applications of deep learning algorithms in lung cancer diagnosis and prognosis. DISCUSSION AND CONCLUSION: With the advance of technology, digital pathology could have great potential impacts in lung cancer patient care. We point out some promising future directions for lung cancer pathology image analysis, including multi-task learning, transfer learning, and model interpretation.

Membrane carbonic anhydrase IX expression and relapse risk in resected stage I-II non-small-cell lung cancer.

BACKGROUND: Adjuvant chemotherapy reduces recurrences of non-small-cell lung cancer (NSCLC). To determine which patients need adjuvant chemotherapy, we assessed factors associated with time to relapse (TTR). METHODS: In 230 resected stage I-II NSCLCs, we correlated immunohistochemistry scores for factors associated with cell growth rate, growth regulation, hypoxia, cell survival, and cell death with TTR. RESULTS: With a median follow-up of 82 months (1-158) for those alive and relapse free at last follow-up, median time to recurrence was not reached. The 2- and 5-year probabilities of maintaining freedom from recurrence were 80.7% (95% confidence interval, 75.3%, 86.4%) and 74.6% (95% confidence interval, 68.6%, 81.2%), respectively. TTR curves flattened at an apparent cure rate of 70%. In multicovariate Cox models, factors correlating with shorter TTR were membranous carbonic anhydrase IX (mCAIX) staining (any versus none, hazard ratio = 2.083, p = 0.023) and node stage (N1 versus N0, hazard ratio = 2.591, p = 0.002). mCAIX scores correlated positively with tumor size, grade, squamous histology, necrosis, mitoses, Ki67, p53, nuclear DNA methyltransferase 1, and cytoplasmic enhancer-of-split-and-hairy-related protein, and they correlated inversely with papillary histology, epidermal growth factor receptor mutation (trend), copper transporter-1, and cytoplasmic hypoxia-inducible factor-1α, vascular endothelial growth factor, DNA methyltransferase 1, and excision repair cross-complementing rodent repair deficiency, complementation group 1. CONCLUSION: Nodal stage and mCAIX immunohistochemistry were the strongest independent predictors of shorter TTR in resected NSCLCs. mCAIX correlated with tumor size, markers of tumor proliferation and necrosis, and tumor genetic characteristics, and it paradoxically correlated inversely with the hypoxia markers, hypoxia-inducible factor-1α and vascular endothelial growth factor. Presence of mCAIX could help determine patients with high risk of recurrence who might require adjuvant chemotherapy.

Prognostic value of LIPC in non-small cell lung carcinoma.

Non-small cell lung carcinoma (NSCLC) is the most common form of lung cancer and is associated with a high mortality rate worldwide. The majority of individuals bearing NSCLC are treated with surgery plus adjuvant cisplatin, an initially effective therapeutic regimen that, however, is unable to prevent relapse within 5 years after tumor resection in an elevated proportion of patients. The factors that predict the clinical course of NSCLC and its sensitivity to therapy remain largely obscure. One notable exception is provided by pyridoxal kinase (PDXK), the enzyme that generates the bioactive form of vitamin B6. PDXK has recently been shown to be required for optimal cisplatin responses in vitro and in vivo and to constitute a bona fide prognostic marker in the NSCLC setting. Together with PDXK, 84 additional factors were identified that influence the response of NSCLC cells to cisplatin, in vitro including the hepatic lipase LIPC. Here, we report that the intratumoral levels of LIPC, as assessed by immunohistochemistry in two independent cohorts of NSCLC patients, positively correlate with disease outcome. In one out of two cohorts studied, the overall survival of NSCLC patients bearing LIPChigh lesions was unaffected, if not slightly worsened, by cisplatin-based adjuvant therapy. Conversely, the overall survival of patients with LIPClow lesions was prolonged by post-operative cisplatin. Pending validation in appropriate clinical series, these results suggest that LIPClow NSCLC patients would be those who mainly benefit from adjuvant cisplatin therapy. Thus, the expression levels of LIPC appear to have an independent prognostic value (and perhaps a predictive potential) in the setting of NSCLC. If these findings were confirmed by additional studies, LIPC expression levels might allow not only for NSCLC patient stratification, but also for the implementation of personalized therapeutic approaches.

Mechanistic contribution of ubiquitous 15-lipoxygenase-1 expression loss in cancer cells to terminal cell differentiation evasion.

Loss of terminal cell differentiation promotes tumorigenesis. 15-Lipoxygenase-1 (15-LOX-1) contributes to terminal cell differentiation in normal cells. The mechanistic significance of 15-LOX-1 expression loss in human cancers to terminal cell differentiation suppression is unknown. In a screen of 128 cancer cell lines representing more than 20 types of human cancer, we found that 15-LOX-1 mRNA expression levels were markedly lower than levels in terminally differentiated cells. Relative expression levels of 15-LOX-1 (relative to the level in terminally differentiated primary normal human-derived bronchial epithelial cells) were lower in 79% of the screened cancer cell lines than relative expression levels of p16 (INK4A), which promotes terminal cell differentiation and is considered one of the most commonly lost tumor suppressor genes in cancer cells. 15-LOX-1 was expressed during terminal differentiation in three-dimensional air-liquid interface cultures, and 15-LOX-1 expression and terminal differentiation occurred in immortalized nontransformed bronchial epithelial but not in lung cancer cell lines. 15-LOX-1 expression levels were lower in human tumors than in paired normal lung epithelia. Short hairpin RNA-mediated downregulation of 15-LOX-1 in Caco-2 cells blocked enterocyte-like differentiation, disrupted tight junction formation, and blocked E-cadherin and ZO-1 localization to the cell wall membrane. 15-LOX-1 episomal expression in Caco-2 and HT-29 colon cancer cells induced differentiation. Our findings indicate that 15-LOX-1 downregulation in cancer cells is an important mechanism for terminal cell differentiation dysregulation and support the potential therapeutic utility of 15-LOX-1 reexpression to inhibit tumorigenesis.