MicroSEC filters sequence errors for formalin-fixed and paraffin-embedded samples

The evolution of lung adenocarcinoma precursors is associated with chromosomal instability and transition from innate to adaptive immune response/evasion

Studying lung adenocarcinoma (LUAD) early carcinogenesis is challenging, primarily due to the lack of LUAD precursors specimens. We amassed multi-omics data from 213 LUAD and LUAD precursors to identify molecular features underlying LUAD precancer evolution. We observed progressively increasing mutations, chromosomal aberrations, whole genome doubling and genomic instability from precancer to invasive LUAD, indicating aggravating chromosomal instability (CIN). Telomere shortening, a crucial genomic alteration linked to CIN, emerged at precancer stage. Moreover, later-stage lesions demonstrated increasing cancer stemness and decreasing alveolar identity, suggesting epithelial de-differentiation during early LUAD carcinogenesis. The innate immune cells progressively diminished from precancer to invasive LUAD, concomitant with a gradual recruitment of adaptive immune cells (except CD8+ and gamma-delta T cells that decreased in later stages) and upregulation of numerous immune checkpoints, suggesting LUAD precancer evolution is associated with a shift from innate to adaptive immune response and immune evasion mediated by various mechanisms.

Strategic Approach to Heterogeneity Analysis of Cutaneous Adnexal Carcinomas Using Computational Pathology and Genomics

Cutaneous adnexal tumors are neoplasms that arise from skin appendages. Their morphologic diversity and phenotypic variability with rare progression to malignancy make them difficult to diagnose and classify, and there is currently no established treatment strategy. To overcome these difficulties, this study investigated the transcription factor SOX9 expression, morphology, and genetics of skin adnexal tumors for understanding their biology, especially their histogenesis. We showed that cutaneous adnexal tumors and their nontumor counterparts of skin and appendages exhibit expression patterns similar to that of SOX9. Its expression intensity and pattern, as well as histopathologic evaluation of tumors, were analyzed using digital images of 69 normal skin adnexal 9-type organs and 185 skin adnexal 29-type tumors as references. It was possible to distinguish basal cell carcinoma from squamous cell carcinoma, sebaceous carcinoma, and pilomatrixoma with significant differences, along with porocarcinoma from squamous cell carcinoma. Furthermore, unsupervised machine learning "computational pathology" was used to derive a multiregion whole-exome sequencing fusion method termed "genocomputed pathology." The genocomputed pathology of three representable adnexal carcinomas (porocarcinoma, hidradenocarcinoma, and spiradenocarcinoma) was evaluated for total nine cases. We showed that there was more heterogeneity than expected within the tumors as well as the coexistence of components lacking driver fusion genes. The presence or absence of potential driver genes, such as PIK3CA, YAP1, and PTEN, in each region was identified, highlighting a therapeutic strategy for cutaneous adnexal carcinoma encompassing heterogeneous tumors.

Tumor mutational burden measurement using comprehensive genomic profiling assay

BACKGROUND

Tumors with a high number of mutations in the genome, or tumor mutational burden, are presumed to be more likely to respond to immune checkpoint inhibitors. However, the optimal method to calculate tumor mutational burden using comprehensive genomic profiling assays is unknown.

METHODS

Todai OncoPanel is a dual panel of a deoxyribonucleic acid panel and a ribonucleic acid panel. Todai OncoPanel deoxyribonucleic acid panel version 6 is an improvement over version 3 with increased number of targeted genes and limited targeting of intronic regions. We calculated tumor mutational burden measured by Todai OncoPanel deoxyribonucleic acid panel versions 3 and 6 using three different calculation methods: all mutations within the targeted region (target tumor mutational burden), all mutations within the coding region (all coding tumor mutational burden) and non-synonymous mutations (non-synonymous coding tumor mutational burden). We then compared them with whole exosome sequencing tumor mutational burden. In addition, 16 lung cancer patients whose samples were analyzed using Todai OncoPanel deoxyribonucleic acid version 3 were treated with anti-PD-1 or PD-L1 antibody monotherapy.

RESULTS

When compared with whole exosome sequencing tumor mutational burden as the standard, tumor mutational burden measured by Todai OncoPanel deoxyribonucleic acid version 3 resulted in accuracy of 71% for all three calculation methods. In version 6, accuracy was 96% for target tumor mutational burden and all coding tumor mutational burden and 91% for non-synonymous coding tumor mutational burden. Patients with either partial response or stable disease had higher non-synonymous coding tumor mutational burden (6.7/Mb vs. 1.6/Mb, P = 0.02) and higher PD-L1 expression (40% vs. 3%, P = 0.01) and a trend toward higher target tumor mutational burden (9.2/Mb vs. 2.4/Mb, P = 0.09) compared with patients with progressive disease.

CONCLUSIONS

Increase in targeted gene number and limiting intronic regions improved tumor mutational burden measurement by Todai OncoPanel when compared with whole exosome sequencing tumor mutational burden. Target tumor mutational burden may be the method of choice to measure tumor mutational burden.