A collaborative workflow between pathologists and deep learning for the evaluation of tumour cellularity in lung adenocarcinoma

AIMS

The reporting of tumour cellularity in cancer samples has become a mandatory task for pathologists. However, the estimation of tumour cellularity is often inaccurate. Therefore, we propose a collaborative workflow between pathologists and artificial intelligence (AI) models to evaluate tumour cellularity in lung cancer samples and propose a protocol to apply it to routine practice.

METHODS AND RESULTS

We developed a quantitative model of lung adenocarcinoma that was validated and tested on 50 cases, and a collaborative workflow where pathologists could access the AI results and adjust their original tumour cellularity scores (adjusted-score) that we tested on 151 cases. The adjusted-score was validated by comparing them with a ground truth established by manual annotation of haematoxylin and eosin slides with reference to immunostains with thyroid transcription factor-1 and napsin A. For training, validation, testing the AI and testing the collaborative workflow, we used 40, 10, 50 and 151 whole slide images of lung adenocarcinoma, respectively. The sensitivity and specificity of tumour segmentation were 97 and 87%, respectively, and the accuracy of nuclei recognition was 99%. One pathologist's visually estimated scores were compared to the adjusted-score, and the pathologist's scores were altered in 87% of cases. Comparison with the ground truth revealed that the adjusted-score was more precise than the pathologists' scores (P < 0.05).

CONCLUSION

We proposed a collaborative workflow between AI and pathologists as a model to improve daily practice and enhance the prediction of tumour cellularity for genetic tests.

Cold and heterogeneous T cell repertoire is associated with copy number aberrations and loss of immune genes in small-cell lung cancer

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.

Immune evolution from preneoplasia to invasive lung adenocarcinomas and underlying molecular features

The mechanism by which anti-cancer immunity shapes early carcinogenesis of lung adenocarcinoma (ADC) is unknown. In this study, we characterize the immune contexture of invasive lung ADC and its precursors by transcriptomic immune profiling, T cell receptor (TCR) sequencing and multiplex immunofluorescence (mIF). Our results demonstrate that anti-tumor immunity evolved as a continuum from lung preneoplasia, to preinvasive ADC, minimally-invasive ADC and frankly invasive lung ADC with a gradually less effective and more intensively regulated immune response including down-regulation of immune-activation pathways, up-regulation of immunosuppressive pathways, lower infiltration of cytotoxic T cells (CTLs) and anti-tumor helper T cells (Th), higher infiltration of regulatory T cells (Tregs), decreased T cell clonality, and lower frequencies of top T cell clones in later-stages. Driver mutations, chromosomal copy number aberrations (CNAs) and aberrant DNA methylation may collectively impinge host immune responses and facilitate immune evasion, promoting the outgrowth of fit subclones in preneoplasia into dominant clones in invasive ADC.

Evolution of DNA methylome from precancerous lesions to invasive lung adenocarcinomas

The evolution of DNA methylome and methylation intra-tumor heterogeneity (ITH) during early carcinogenesis of lung adenocarcinoma has not been systematically studied. We perform reduced representation bisulfite sequencing of invasive lung adenocarcinoma and its precursors, atypical adenomatous hyperplasia, adenocarcinoma in situ and minimally invasive adenocarcinoma. We observe gradual increase of methylation aberrations and significantly higher level of methylation ITH in later-stage lesions. The phylogenetic patterns inferred from methylation aberrations resemble those based on somatic mutations suggesting parallel methylation and genetic evolution. De-convolution reveal higher ratio of T regulatory cells (Tregs) versus CD8 + T cells in later-stage diseases, implying progressive immunosuppression with neoplastic progression. Furthermore, increased global hypomethylation is associated with higher mutation burden, copy number variation burden and AI burden as well as higher Treg/CD8 ratio, highlighting the potential impact of methylation on chromosomal instability, mutagenesis and tumor immune microenvironment during early carcinogenesis of lung adenocarcinomas.

Clinicopathological significance of the expression of PD-L1 in non-small cell lung cancer

INTRODUCTION

PD1/PD-L1 pathway targeting therapies are nowadays an established treatment option for patients with NSCLC. We assessed whether PD-L1 expression in NSCLC tumor cells was associated with specific clinical features or overall survival using four different clones.

METHODS AND RESULTS

A retrospective study included formalin-fixed paraffin embedded (FFPE) surgical tumors from 482 patients. PD-L1 status was assessed with immunohistochemistry in tumor cells on tissue microarrays using clones 28-8, 22C3, SP263 and SP142. Associations with OS were assessed by Kaplan-Meier and multivariate Cox's regression analysis. Patients' median age: 68 years (39-86); histology: adenocarcinoma (AdCa) 61%, squamous-cell carcinoma (SqCC) 33%, and large cell carcinoma (LCC) 6%; p-stage: IA (46%), IB (30%), IIA (10%), IIB (11,4%), IIIA (1,2%), IIIB - IV (0,4%). PD-L1 positivity (≥1%) in NSCLC for clones 28-8, 22C3, SP263, SP142 was 41.5%, 34.2%, 42.7%, 10.4%, respectively (Pearson Chi-square p < 0.0001). PD-L1 expression was correlated with histology, tumor size and grading. Statistically significant association between PD-L1 expression and OS in NSCLC and Non-AdCa was observed with clone SP142 (log-rank p = 0.045 and p = 0.05, respectively). Statistically significant association between PD-L1 expression and OS in LCC was observed with clones 22C3 (log-rank p = 0.009) and SP263 (log-rank p = 0.050).

CONCLUSIONS

Overexpression of the PD-L1 clone SP142 was associated with poor overall survival in NSCLC and Non-AdCa. Clones 22C3 and SP263 were associated with poor prognosis in LCC. PD-L1 status might serve as a prognostic marker in NSCLC.