Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma.

Molecular subtyping of lung squamous cell carcinoma (LUSC) has been performed at the genomic, transcriptomic, and proteomic level. However, LUSC stratification based on tissue metabolomics is still lacking. Combining high-mass-resolution imaging mass spectrometry with consensus clustering, four tumor- and four stroma-specific subtypes with distinct metabolite patterns were identified in 330 LUSC patients. The first tumor subtype T1 negatively correlated with DNA damage and immunological features including CD3, CD8, and PD-L1. The same features positively correlated with the tumor subtype T2. Tumor subtype T4 was associated with high PD-L1 expression. Compared with the status of subtypes T1 and T4, patients with subtype T3 had improved prognosis, and T3 was an independent prognostic factor with regard to UICC stage. Similarly, stroma subtypes were linked to distinct immunological features and metabolic pathways. Stroma subtype S4 had a better prognosis than S2. Subsequently, analyses based on an independent LUSC cohort treated by neoadjuvant therapy revealed that the S2 stroma subtype was associated with chemotherapy resistance. Clinically relevant patient subtypes as determined by tissue-based spatial metabolomics are a valuable addition to existing molecular classification systems. Metabolic differences among the subtypes and their associations with immunological features may contribute to the improvement of personalized therapy.

Patterns of Carbon-Bound Exogenous Compounds Impact Disease Pathophysiology in Lung Cancer Subtypes in Different Ways.

Carbon-bound exogenous compounds, such as polycyclic aromatic hydrocarbons (PAHs), tobacco-specific nitrosamines, aromatic amines, and organohalogens, are known to affect both tumor characteristics and patient outcomes in lung squamous cell carcinoma (LUSC); however, the roles of these compounds in lung adenocarcinoma (LUAD) remain unclear. We analyzed 11 carbon-bound exogenous compounds in LUAD and LUSC samples using in situ high mass-resolution matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging and performed a cluster analysis to compare the patterns of carbon-bound exogenous compounds between these two lung cancer subtypes. Correlation analyses were conducted to investigate associations among exogenous compounds, endogenous metabolites, and clinical data, including patient survival outcomes and smoking behaviors. Additionally, we examined differences in exogenous compound patterns between normal and tumor tissues. Our analyses revealed that PAHs, aromatic amines, and organohalogens were more abundant in LUAD than in LUSC, whereas the tobacco-specific nitrosamine nicotine-derived nitrosamine ketone was more abundant in LUSC. Patients with LUAD and LUSC could be separated according to carbon-bound exogenous compound patterns detected in the tumor compartment. The same compounds had differential impacts on patient outcomes, depending on the cancer subtype. Correlation and network analyses indicated substantial differences between LUAD and LUSC metabolomes, associated with substantial differences in the patterns of the carbon-bound exogenous compounds. These data suggest that the contributions of these carcinogenic compounds to cancer biology may differ according to the cancer subtypes.

Deep computational image analysis of immune cell niches reveals treatment-specific outcome associations in lung cancer.

The tumor immune composition influences prognosis and treatment sensitivity in lung cancer. The presence of effective adaptive immune responses is associated with increased clinical benefit after immune checkpoint blockers. Conversely, immunotherapy resistance can occur as a consequence of local T-cell exhaustion/dysfunction and upregulation of immunosuppressive signals and regulatory cells. Consequently, merely measuring the amount of tumor-infiltrating lymphocytes (TILs) may not accurately reflect the complexity of tumor-immune interactions and T-cell functional states and may not be valuable as a treatment-specific biomarker. In this work, we investigate an immune-related biomarker (PhenoTIL) and its value in associating with treatment-specific outcomes in non-small cell lung cancer (NSCLC). PhenoTIL is a novel computational pathology approach that uses machine learning to capture spatial interplay and infer functional features of immune cell niches associated with tumor rejection and patient outcomes. PhenoTIL's advantage is the computational characterization of the tumor immune microenvironment extracted from H&E-stained preparations. Association with clinical outcome and major non-small cell lung cancer (NSCLC) histology variants was studied in baseline tumor specimens from 1,774 lung cancer patients treated with immunotherapy and/or chemotherapy, including the clinical trial Checkmate 057 (NCT01673867).

Integrated longitudinal analysis of adult grade 4 diffuse gliomas with long-term relapse interval revealed upregulation of TGF-ß signaling in recurrent tumors.

BACKGROUND: Adult-type diffuse gliomas, CNS WHO grade 4 are the most aggressive primary brain tumors and represent a particular challenge for therapeutic intervention. METHODS: In a single-center retrospective study of matched pairs of initial and post-therapeutic glioma cases with a recurrence period greater than 1 year, we performed whole exome sequencing combined with mRNA and microRNA expression profiling to identify processes that are altered in recurrent gliomas. RESULTS: Mutational analysis of recurrent gliomas revealed early branching evolution in 75% of the patients. High plasticity was confirmed at the mRNA and miRNA levels. SBS1 signature was reduced and SBS11 was elevated, demonstrating the effect of alkylating agent therapy on the mutational landscape. There was no evidence for secondary genomic alterations driving therapy resistance. ALK7/ACVR1C and LTBP1 were upregulated, whereas LEFTY2 was downregulated, pointing towards enhanced Tumor Growth Factor ß (TGF-ß) signaling in recurrent gliomas. Consistently, altered microRNA expression profiles pointed towards enhanced Nuclear Factor Kappa B and Wnt signaling that, cooperatively with TGF-ß, induces epithelial to mesenchymal transition (EMT), migration, and stemness. TGF-ß-induced expression of pro-apoptotic proteins and repression of antiapoptotic proteins were uncoupled in the recurrent tumor. CONCLUSIONS: Our results suggest an important role of TGF-ß signaling in recurrent gliomas. This may have clinical implications since TGF-ß inhibitors have entered clinical phase studies and may potentially be used in combination therapy to interfere with chemoradiation resistance. Recurrent gliomas show high incidence of early branching evolution. High tumor plasticity is confirmed at the level of microRNA and mRNA expression profiles.

Programmed Death-Ligand 1 Expression in Lung Cancer and Paired Brain Metastases-a Single-Center Study in 190 Patients.

Introduction: Expression of programmed death-ligand 1 (PD-L1) is the only routinely used tissue biomarker for predicting response to programmed cell death protein 1/PD-L1 inhibitors. It is to date unclear whether PD-L1 expression is preserved in brain metastases (BMs). Methods: In this single-center, retrospective study, we evaluated PD-L1 expression using the SP263 assay in consecutively resected BMs of lung carcinomas and paired primary tumors, diagnosed from 2000 to 2015, with correlation to clinicopathological and molecular tumor and patient characteristics. Results: PD-L1 tumor proportional score (TPS) could be evaluated on whole tissue slides in 191 BMs and 84 paired primary lung carcinomas. PD-L1 TPS was less than 1% in 113 of 191 (59.2%), 1% to 49% in 34 of 191 (17.8%), and greater than or equal to 50% in 44 of 191 (23.0%) BMs. TPS was concordant between BMs and paired primary lung carcinomas in most cases, with discordance regarding the clinically relevant cutoffs at 1% and 50% in 18 of 84 patients (21.4%). Four of 18 discordant cases had no shared mutations between the primary lung carcinoma and BM. Intratumoral heterogeneity, as assessed using tissue microarray cores, was only significant at the primary site (p Wilcoxon signed rank = 0.002) with higher PD-L1 TPS at the infiltration front (mean = 40.4%, interquartile range: 0%-90%). Neither TPS greater than or equal to 1% nor TPS greater than or equal to 50% nor discordance between the primary lung carcinoma and BMs had prognostic significance regarding overall survival or BM-specific overall survival. Conclusions: PD-L1 expression was mostly concordant between primary lung carcinoma and its BM and between resections of BM and stereotactic biopsies, mirrored by tissue microarray cores. Differences in PD-L1 TPS existed primarily in cases with TPS greater than 10%, for which also human assessment tends to be most error prone.

The effect of neoadjuvant therapy on PD-L1 expression and CD8+lymphocyte density in non-small cell lung cancer.

PD-L1 expression is the routine clinical biomarker for the selection of patients to receive immunotherapy in non-small cell lung cancer (NSCLC). However, the application and best timing of immunotherapy in the resectable setting is still under investigation. We aimed to study the effect of chemotherapy on PD-L1 expression and tumor infiltrating lymphocytes (TILs), which is to date still poorly understood. Our retrospective, single-centre neoadjuvant cohort comprised 96 consecutive patients with NSCLC resected 2000-2016 after neoadjuvant therapy, including paired diagnostic chemo-naïve specimens in 53 cases. A biologically matched surgical cohort of 114 primary resected cases was included. PD-L1 expression, CD8 + TILs density and tertiary lymphoid structures were assessed on whole slides and correlated with clinico-pathological characteristics and survival. Seven/53 and 12/53 cases had lower respectively higher PD-L1 expressions after neoadjuvant therapy. Most cases (n = 34) showed no changes in PD-L1 expression, the majority of these harboring PD-L1 < 1% in both samples (21/34 [61.8%]). Although CD8 + TILs density was significantly higher after chemotherapy (p = 0.031) in resections compared to diagnostic biopsies, this might be due to sampling and statistical bias. No difference in PD-L1 expression or CD8 + TILs density was detected when comparing the neoadjuvant and surgical cohort. In univariable analyses, higher CD8 + TILs density, higher numbers of tertiary lymphoid structures but not PD-L1 expression were significantly associated with longer survival. Increased PD-L1 expression after neoadjuvant chemotherapy was not significantly associated with shorter 5-year survival, but the number of cases was very low. In multivariable analysis, only pT category and age remained independent prognostic factors. In summary, PD-L1 expression was mostly unchanged after neoadjuvant chemotherapy compared to diagnostic biopsies. The sample size of cases with changed PD-L1 expression was too small to draw conclusions on any prognostic value.

Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome.

Despite known histological, biological, and clinical differences between lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), relatively little is known about the spatial differences in their corresponding immune contextures. Our study of over 1000 LUAD and LUSC tumors revealed that computationally derived patterns of tumor-infiltrating lymphocytes (TILs) on H&E images were different between LUAD (N = 421) and LUSC (N = 438), with TIL density being prognostic of overall survival in LUAD and spatial arrangement being more prognostically relevant in LUSC. In addition, the LUAD-specific TIL signature was associated with OS in an external validation set of 100 NSCLC treated with more than six different neoadjuvant chemotherapy regimens, and predictive of response to therapy in the clinical trial CA209-057 (n = 303). In LUAD, the prognostic TIL signature was primarily comprised of CD4+ T and CD8+ T cells, whereas in LUSC, the immune patterns were comprised of CD4+ T, CD8+ T, and CD20+ B cells. In both subtypes, prognostic TIL features were associated with transcriptomics-derived immune scores and biological pathways implicated in immune recognition, response, and evasion. Our results suggest the need for histologic subtype-specific TIL-based models for stratifying survival risk and predicting response to therapy. Our findings suggest that predictive models for response to therapy will need to account for the unique morphologic and molecular immune patterns as a function of histologic subtype of NSCLC.

Spatial metabolomics for evaluating response to neoadjuvant therapy in non-small cell lung cancer patients.

BACKGROUND: The response to neoadjuvant chemotherapy (NAC) differs substantially among individual patients with non-small cell lung cancer (NSCLC). Major pathological response (MPR) is a histomorphological read-out used to assess treatment response and prognosis in patients NSCLC after NAC. Although spatial metabolomics is a promising tool for evaluating metabolic phenotypes, it has not yet been utilized to assess therapy responses in patients with NSCLC. We evaluated the potential application of spatial metabolomics in cancer tissues to assess the response to NAC, using a metabolic classifier that utilizes mass spectrometry imaging combined with machine learning. METHODS: Resected NSCLC tissue specimens obtained after NAC (n = 88) were subjected to high-resolution mass spectrometry, and these data were used to develop an approach for assessing the response to NAC in patients with NSCLC. The specificities of the generated tumor cell and stroma classifiers were validated by applying this approach to a cohort of biologically matched chemotherapy-naïve patients with NSCLC (n = 85). RESULTS: The developed tumor cell metabolic classifier stratified patients into different prognostic groups with 81.6% accuracy, whereas the stroma metabolic classifier displayed 78.4% accuracy. By contrast, the accuracies of MPR and TNM staging for stratification were 62.5% and 54.1%, respectively. The combination of metabolic and MPR classifiers showed slightly lower accuracy than either individual metabolic classifier. In multivariate analysis, metabolic classifiers were the only independent prognostic factors identified (tumor: P = 0.001, hazards ratio [HR] = 3.823, 95% confidence interval [CI] = 1.716-8.514; stroma: P = 0.049, HR = 2.180, 95% CI = 1.004-4.737), whereas MPR (P = 0.804; HR = 0.913; 95% CI = 0.445-1.874) and TNM staging (P = 0.078; HR = 1.223; 95% CI = 0.977-1.550) were not independent prognostic factors. Using Kaplan-Meier survival analyses, both tumor and stroma metabolic classifiers were able to further stratify patients as NAC responders (P < 0.001) and non-responders (P < 0.001). CONCLUSIONS: Our findings indicate that the metabolic constitutions of both tumor cells and the stroma are valuable additions to the classical histomorphology-based assessment of tumor response.

Tumor-infiltrating lymphocytes are functionally inactivated by CD90+ stromal cells and reactivated by combined Ibrutinib and Rapamycin in human pleural mesothelioma.

Rationale: Despite evidence suggesting that the tumor microenvironment (TME) in malignant pleural mesothelioma (MPM) is linked with poor prognosis, there is a lack of studies that functionally characterize stromal cells and tumor-infiltrating lymphocytes (TILs). Here, we aim to characterize the stromal subsets within MPM, investigate their relationship to TILs, and explore the potential therapeutic targets. Methods: We curated a core set of genes defining stromal/immune signatures expressed by mesenchymal cells within the TME using molecular analysis of The Cancer Genome Atlas (TCGA) MPM cohort. Stromal and immune profiles were molecularly characterized using flow cytometry, immunohistochemistry, microarray, and functionally evaluated using T cell-activation/expansion, coculture assays and drug compounds treatment, based on samples from an independent MPM cohort. Results: We found that a high extracellular matrix (ECM)/stromal gene signature, a high ECM score, or the ratio of ECM to an immune activation gene signature are significantly associated with poor survival in the MPM cohort in TCGA. Analysis of an independent MPM cohort (n = 12) revealed that CD8+ and CD4+ TILs were characterized by PD1 overexpression and concomitant downregulation in degranulation and CD127. This coincided with an increase in CD90+ cells that overexpressed PD-L1 and were enriched for ECM/stromal genes, activated PI3K-mTOR signaling and suppressed T cells. Protein array data demonstrated that MPM samples with high PD-L1 expression were most associated with activation of the mTOR pathway. Further, to reactivate functionally indolent TILs, we reprogrammed ex vivo TILs with Ibrutinib plus Rapamycin to block interleukin-2-inducible kinase (ITK) and mTOR pathways, respectively. The combination treatment shifted effector memory (TEM) CD8+ and CD4+ TILs towards T cells that re-expressed CD45RA (TEMRA) while concomitantly downregulating exhaustion markers. Gene expression analysis confirmed that Ibrutinib plus Rapamycin downregulated coinhibitory and T cell signature pathways while upregulating pathways involved in DNA damage and repair and immune cell adhesion and migration. Conclusions: Our results suggest that targeting the TME may represent a novel strategy to redirect the fate of endogenous TILs with the goal of restoring anti-tumor immunity and control of tumor growth in MPM.

Mutational profiles of primary pulmonary adenocarcinoma and paired brain metastases disclose the importance of KRAS mutations.

BACKGROUND: Brain metastases present a significant complication in lung cancer with an unmet therapeutic need. METHODS: In this single-centre, retrospective study, we genotyped a clinico-pathologically well-annotated cohort of consecutively resected brain metastases of lung adenocarcinomas and paired primary tumours, diagnosed from 2000 to 2015, using the Ion Torrent Oncomine Comprehensive Cancer Panel v3. RESULTS: Among 444 consecutive brain metastases, 210 (49%) originated from lung cancer. Analysis was successful in 111 samples, including 54 pairs of brain metastasis and primary tumour. Most driver alterations were preserved in brain metastases. Private alterations exclusive to primary tumours, brain metastases or both sites (intersecting cases) were present in 22%, 26% and 26% of cases, respectively. Seven percent had no shared mutations. KRAS mutations were more frequent in primary tumours metastasised to the brain (32/55, 58%) compared to TCGA (33%, p < 0.005) and own data from routine diagnostics, independent from clinical or pathological characteristics. Fourteen cases showed alterations in the EGFR signalling pathway including additional KRAS alterations that were private to brain metastases. KRAS G12C was detected most frequently (26% of patients) and KRAS G12C and G13C variants were significantly enriched in brain metastases. Synchronous and metachronous cases had a similar mutation profile. CONCLUSIONS: Our results suggest an important role of KRAS alterations in the pathobiology of brain metastases from lung adenocarcinomas. This has direct therapeutic implications as inhibitors selectively targeting KRAS G12C are entering the clinics.

Chaperone-Mediated Autophagy Markers LAMP2A and HSPA8 in Advanced Non-Small Cell Lung Cancer after Neoadjuvant Therapy.

In recent years autophagy has attracted the attention of researchers from many medical fields, including cancer research, and certain anti-macroautophagy drugs in combination with cytotoxic or targeted therapies have entered clinical trials. In the present study, we focused on a less explored subtype of autophagy, i.e., chaperone-mediated autophagy (CMA), with the key proteins LAMP2A and HSPA8 (HSC70), and their immunohistochemical evaluation with previously extensively validated antibodies. We were interested in whether the marker expression is influenced by the antecedent therapy, and its correlation with survival on a cohort of patients with non-small cell lung cancer (NSCLC) after neoadjuvant therapy and matched primary resected tumors. In concordance with our previous study, we did not find any intratumoral heterogeneity, nor correlation between the two parameters, nor correlation between the markers and any included pathological parameters. Surprisingly, the expression of both markers was also independent to tumor response or administered neoadjuvant treatment. In the survival analysis, the results were only significant for LAMP2A, where higher levels were associated with longer 5-year overall survival and disease-free survival for the mixed group of adenocarcinomas and squamous cell carcinomas (p < 0.0001 and p = 0.0019 respectively) as well as the squamous cell carcinoma subgroup (p = 0.0001 and p = 0.0001 respectively). LAMP2A was also an independent prognostic marker in univariate and multivariate analysis.

Chemotherapy-induced CDA expression renders resistant non-small cell lung cancer cells sensitive to 5'-deoxy-5-fluorocytidine (5'-DFCR).

BACKGROUND: Pemetrexed (MTA) plus cisplatin combination therapy is considered the standard of care for patients with advanced non-small-cell lung cancer (NSCLC). However, in advanced NSCLC, the 5-year survival rate is below 10%, mainly due to resistance to therapy. We have previously shown that the fraction of mesenchymal-like, chemotherapy-resistant paraclone cells increased after MTA and cisplatin combination therapy in the NSCLC cell line A549. Cytidine deaminase (CDA) and thymidine phosphorylase (TYMP) are key enzymes of the pyrimidine salvage pathway. 5'-deoxy-5-fluorocytidine (5'-DFCR) is a cytidine analogue (metabolite of capecitabine), which is converted by CDA and subsequently by TYMP into 5-fluorouracil, a chemotherapeutic agent frequently used to treat solid tumors. The aim of this study was to identify and exploit chemotherapy-induced metabolic adaptations to target resistant cancer cells. METHODS: Cell viability and colony formation assays were used to quantify the efficacy of MTA and cisplatin treatment in combination with schedule-dependent addition of 5'-DFCR on growth and survival of A549 paraclone cells and NSCLC cell lines. CDA and TYMP protein expression were monitored by Western blot. Finally, flow cytometry was used to analyze the EMT phenotype, DNA damage response activation and cell cycle distribution over time after treatment. CDA expression was measured by immunohistochemistry in tumor tissues of patients before and after neoadjuvant chemotherapy. RESULTS: We performed a small-scale screen of mitochondrial metabolism inhibitors, which revealed that 5'-DFCR selectively targets chemotherapy-resistant A549 paraclone cells characterized by high CDA and TYMP expression. In the cell line A549, CDA and TYMP expression was further increased by chemotherapy in a time-dependent manner, which was also observed in the KRAS-addicted NSCLC cell lines H358 and H411. The addition of 5'-DFCR on the second day after MTA and cisplatin combination therapy was the most efficient treatment to eradicate chemotherapy-resistant NSCLC cells. Moreover, recovery from treatment-induced DNA damage was delayed and accompanied by senescence induction and acquisition of a hybrid-EMT phenotype. In a subset of patient tumors, CDA expression was also increased after treatment with neoadjuvant chemotherapy. CONCLUSIONS: Chemotherapy increases CDA and TYMP expression thereby rendering resistant lung cancer cells susceptible to subsequent 5'-DFCR treatment.

A prognostic score for non-small cell lung cancer resected after neoadjuvant therapy in comparison with the tumor-node-metastases classification and major pathological response.

Studies validating the prognostic accuracy of the tumor-node-metastases (TNM) classification in patients with lung cancer treated by neoadjuvant therapy are scarce. Tumor regression, particularly major pathological response (MPR), is an acknowledged prognostic factor in this setting. We aimed to validate a novel combined prognostic score. This retrospective single-center study was conducted on 117 consecutive patients with non-small cell lung cancer resected after neoadjuvant treatment at a Swiss University Cancer Center between 2000 and 2016. All cases were clinicopathologically re-evaluated. We assessed the prognostic performance of a novel prognostic score (PRSC) combining T-category, lymph node status, and MPR, in comparison with the eighth edition of the TNM classification (TNM8), the size adapted TNM8 as proposed by the International Association for the Study of Lung Cancer (IASLC) and MPR alone. The isolated ypT-category and the combined TNM8 stages accurately differentiated overall survival (OS, stage p = 0.004) and disease-free survival (DFS, stage p = 0.018). Tumor regression had a prognostic impact. Optimal cut-offs for MPR emerged as 65% for adenocarcinoma and 10% for non-adenocarcinoma and were statistically significant for survival (OS p = 0.006, DFS p < 0.001). The PRSC differentiated between three prognostic groups (OS and DFS p < 0.001), and was superior compared to the stratification using MPR alone or the TNM8 systems, visualized by lower Akaike (AIC) and Bayesian information criterion (BIC) values. In the multivariate analyses, stage III tumors (HR 4.956, p = 0.003), tumors without MPR (HR 2.432, p = 0.015), and PRSC high-risk tumors (HR 5.692, p < 0.001) had significantly increased risks of occurring death. In conclusion, we support 65% as the optimal cut-off for MPR in adenocarcinomas. TNM8 and MPR were comparable regarding their prognostic significance. The novel prognostic score performed distinctly better regarding OS and DFS.