Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

Early-stage lung adenocarcinoma (LUAD) patients remain at substantial risk for recurrence and disease-related death, highlighting the unmet need of biomarkers for the assessment and identification of those in an early stage who would likely benefit from adjuvant chemotherapy. To identify circulating miRNAs useful for predicting recurrence in early-stage LUAD, we performed miRNA microarray analysis with pools of pretreatment plasma samples from patients with stage I LUAD who developed recurrence or remained recurrence-free during the follow-up period. Subsequent validation in 85 patients with stage I LUAD resulted in the development of a circulating miRNA panel comprising miR-23a-3p, miR-320c, and miR-125b-5p and yielding an area under the curve (AUC) of 0.776 in predicting recurrence. Furthermore, the three-miRNA panel yielded an AUC of 0.804, with a sensitivity of 45.8% at 95% specificity in the independent test set of 57 stage I and II LUAD patients. The miRNA panel score was a significant and independent factor for predicting disease-free survival (p < 0.001, hazard ratio [HR] = 1.64, 95% confidence interval [CI] = 1.51–4.22) and overall survival (p = 0.001, HR = 1.51, 95% CI = 1.17–1.94). This circulating miRNA panel is a useful noninvasive tool to stratify early-stage LUAD patients and determine an appropriate treatment plan with maximal efficacy.

PDF file - 49K, Multivariate Cox regression analysis of the 18-hub-gene prognostic signature and clinical variables in the UT Lung SPORE.

PDF file - 129K, Sweave report depicting complete codes use for microarray analysis of paired adjacent and contralateral airways

PDF file - 3533K, Sweave report depicting complete codes used for quality control of microarray analysis

PDF file - 108K, Comparison with the gene signatures with other signatures.

Our understanding of the molecular mechanisms underlying postsurgical recurrence of non-small cell lung cancer (NSCLC) is rudimentary. Molecular and T cell repertoire intratumor heterogeneity (ITH) have been reported to be associated with postsurgical relapse; however, how ITH at the cellular level impacts survival is largely unknown. Here we report the analysis of 2880 multispectral images representing 14.2% to 27% of tumor areas from 33 patients with stage I NSCLC, including 17 cases (relapsed within 3 years after surgery) and 16 controls (without recurrence >= 5 years after surgery) using multiplex immunofluorescence. Spatial analysis was conducted to quantify the minimum distance between different cell types and immune cell infiltration around malignant cells. Immune ITH was defined as the variance of immune cells from 3 intratumor regions. We found that tumors from patients having relapsed display different immune biology compared with nonrecurrent tumors, with a higher percentage of tumor cells and macrophages expressing PD-L1 (P =.031 and P =.024, respectively), along with an increase in regulatory T cells (Treg) (P =.018), antigen-experienced T cells (P =.025), and effector-memory T cells (P =.041). Spatial analysis revealed that a higher level of infiltration of PD-L1+ macrophages (CD68+PD-L1+) or antigen-experienced cytotoxic T cells (CD3(+)CD8(+)PD-1(+)) in the tumor was associated with poor overall survival (P =.021 and P =.006, respectively). A higher degree of Treg ITH was associated with inferior recurrence-free survival regardless of tumor mutational burden (P =.022), neoantigen burden (P =.021), genomic ITH (P =.012) and T cell repertoire ITH (P =.001). Using multiregion multiplex immunofluorescence, we characterized ITH at the immune cell level along with whole exome and T cell repertoire sequencing from the same tumor regions. This approach highlights the role of immunoregulatory and coinhibitory signals as well as their spatial distribution and ITH that define the hallmarks of tumor relapse of stage I NSCLC. (c) 2022 United States & Canadian Academy of Pathology. Published by Elsevier Inc. All rights reserved.

Figure S1. Biphasic histologic components of sarcomatoid renal cell carcinoma. The macrodissected paired epithelioid or carcinomatous (E) and spindled or sarcomatoid (S) components of clear cell RCC (upper panel), Papillary RCC (middle panel), and chromophobe RCC (lower panel). H&E stain, scale bar 200 ï­m. Figure S2. Sarcomatoid ccRCC shows fewer VHL deletions. (A) Clear cell RCC (H&E stain, scale bar 100 µm) with (B) Fluorescence in situ hybridization (FISH) image showing paired CEN3q signals (green) and a single VHL signal (red). (C) Sarcomatoid ccRCC (H&E stain, scale bar 100 µm) with (D) FISH image showing balanced CEN3q (green) and VHL (red) signals. (E) Box plot showing significantly higher VHL/3q ratios associated with sarcomatoid histology, P<0.008. Figure S3: The smooth scatter plot of signal B versus signal A. Figure S4a: 3p21 and 3p21.1 copy number versus chromosome position. Figure S4b: 3p25 copy number versus chromosome position. Figure S5: Kernel density plots. Each sample per row; left three columns: 3p21; middle three columns: 2q37; and right three columns: 1p1. Figure S6a: Example of more than one peak in the summed signal. Figure S6b: Example of 4 peaks in signals A and B. Figure S7: Density plots of TCGA samples with copy-neutral LOH. Figure S8. VHL and PBRM1 show fewer 2-hit inactivation in sarcomatoid ccRCC. Sarcomatoid ccRCC and ccRCC cases shown in terms of the inactivating "hits" on 3p21-25 genes (VHL, PBRM1, SETD2, BAP1) consisting of mutations or methylation (mutually exclusive for VHL) and deletions. Figure S9. Top activated and inhibited pathways of sarcomatoid samples. Pathways altered by differentially expressed genes between non-sarcomatoid and sarcomatoid samples. The genes selected were differentially expressed in both the TCGA and MD Anderson samples. Figure S10. S- component shows a higher mutational load in sarcomatoid RCC. The total number of non-synonymous mutations in the E- and S- components of sarcomatoid RCC, across all parent RCC subtypes (A) and in clear cell RCC (B).

Supplementary Figure S1-10 and Table S1

PDF file - 6272K, Sweave report depicting complete codes used for microarray analysis and identification of genes differentially expressed by site and time

PDF file - 104K, Members of the 18-hub gene signature have been included in MSigDB database C2 signature catalogues.

Supplemental Methods 1. Exome sequencing pipeline Supplemental Methods 2. RNA seq pipeline Supplemental Methods 3. DNA methylation profiling pipeline Supplemental Methods 4. Fluorescence in situ hybridization Supplemental Methods 5. TCGA samples with possible copy neutral loss of heterozygosity in 3p21 and 3p25 regions

PDF file - 125K, Histograms of the p-values for site- and time-dependent differential expression; Site-dependent differential gene expression patterns identified by expression profiling of airways excluding main carinas; Smoothened scatter plot of transformed p-values for site and time effects

Supplementary Table 1 - PDF file 57K, Clinicopathological information of the NSCLC tissue microarray specimens analyzed by IHC analysis

Supplementary Figures 1-11 - PDF file 905K, Supplementary Figure 1. Decreased ETS2 expression in smoker lung adenocarcinomas compared to adenocarcinomas from never-smoker patients. Supplementary Figure 2. ETS2 expression in never-smoker and smoker lung cancer cell lines. Supplementary Figure 3. IHC analysis of ETS2 protein in NSCLC FFPE histological tissue specimens. Supplementary Figure 4. Over-expression of ETS2 decreases lung cancer cell anchorage-dependent and -independent growth. Supplementary Figure 5. Modulation of HGF-mediated gene-interaction network following knockdown of ETS2 in H441 lung cancer cells. Supplementary Figure 6. Increased phospho-MET levels following ETS2 knockdown. Supplementary Figure 7. Over-expression of ETS2 decreases MET phosphorylation in lung cancer cells. Supplementary Figure 8. HGF treatment increases ETS2 levels in lung cancer cells. Supplementary Figure 9. ETS2 inhibits HGF-induced lung cancer cell proliferation and migration. Supplementary Figure 10. IHC analysis of phosphorylated MET protein in NSCLC FFPE histological tissue specimens. Supplementary Figure 11. NSCLC patients with both low ETS2 and high membrane phospho-MET IHC expression exhibit significantly reduced time to recurrence

Supplementary Tables 1-3 Supplementary Table 1. Location and number of NSCLC, normal and field of cancerization specimens analyzed for genome-wide allelic imbalance Supplementary Table 2. Summary of identified allelic imbalance events in the normal-appearing airway field of cancerization in early-stage NSCLC Supplementary Table 3. Airway events with negative B-allele frequency correlations

XLSX file - 68K, Supplementary table depicting 1165 genes significantly differentially expressed by site in the molecular field of injury

Background Lung cancer is the leading cause of cancer death, partially owing to its extensive heterogeneity. The analysis of intertumor heterogeneity has been limited by an inability to concurrently obtain tissue from synchronous metastases unaltered by multiple prior lines of therapy. Methods In order to study the relationship between genomic, epigenomic and T cell repertoire heterogeneity in a rare autopsy case from a 32-year-old female never-smoker with left lung primary late-stage lung adenocarcinoma (LUAD), we did whole-exome sequencing (WES), DNA methylation and T cell receptor (TCR) sequencing to characterize the immunogenomic landscape of one primary and 19 synchronous metastatic tumors. Results We observed heterogeneous mutation, methylation, and T cell patterns across distinct metastases. Only TP53 mutation was detected in all tumors suggesting an early event while other cancer gene mutations were later events which may have followed subclonal diversification. A set of prevalent T cell clonotypes were completely excluded from left-side thoracic tumors indicating distinct T cell repertoire profiles between left-side and non left-side thoracic tumors. Though a limited number of predicted neoantigens were shared, these were associated with homology of the T cell repertoire across metastases. Lastly, ratio of methylated neoantigen coding mutations was negatively associated with T-cell density, richness and clonality, suggesting neoantigen methylation may partially drive immunosuppression. Conclusions Our study demonstrates heterogeneous genomic and T cell profiles across synchronous metastases and how restriction of unique T cell clonotypes within an individual may differentially shape the genomic and epigenomic landscapes of synchronous lung metastases.

Small-cell lung cancer (SCLC) is speculated to harbor complex genomic intratumor heterogeneity (ITH) associated with high recurrence rate and suboptimal response to immunotherapy. Here, we revealed a rather homogeneous mutational landscape but extremely suppressed and heterogeneous T cell receptor (TCR) repertoire in SCLCs. Higher mutational burden, lower chromosomal copy number aberration (CNA) burden, less CNA ITH and less TCR ITH were associated with longer overall survival of SCLC patients. Compared to non-small cell lung cancers (NSCLCs), SCLCs had similar predicted neoantigen burden and mutational ITH, but significantly more suppressed and heterogeneous TCR repertoire that may be associated with higher CNA burden and CNA ITH in SCLC. Novel therapeutic strategies targeting CNA could potentially improve the tumor immune microenvironment and response to immunotherapy in SCLC.

Small-cell lung cancer (SCLC) is speculated to harbor complex genomic intratumor heterogeneity (ITH) associated with high recurrence rate and suboptimal response to immunotherapy. Here, using multi-region whole exome/T cell receptor (TCR) sequencing as well as immunohistochemistry, we reveal a rather homogeneous mutational landscape but extremely cold and heterogeneous TCR repertoire in limited-stage SCLC tumors (LS-SCLCs). Compared to localized non-small cell lung cancers, LS-SCLCs have similar predicted neoantigen burden and genomic ITH, but significantly colder and more heterogeneous TCR repertoire associated with higher chromosomal copy number aberration (CNA) burden. Furthermore, copy number loss of IFN-γ pathway genes is frequently observed and positively correlates with CNA burden. Higher mutational burden, higher T cell infiltration and positive PD-L1 expression are associated with longer overall survival (OS), while higher CNA burden is associated with shorter OS in patients with LS-SCLC.