Whole-Exome Sequencing in Papillary Microcarcinoma: Potential Early Biomarkers of Lateral Lymph Node Metastasis

Feasibility of whole-exome sequencing in fine-needle aspiration specimens of papillary thyroid microcarcinoma for the identification of novel gene mutations

Genetic profiling is important for assisting the management of papillary thyroid microcarcinoma (PTMC). Although whole-exome sequencing (WES) of surgically resected PTMC tissue has been performed and revealed potential prognostic biomarkers, its application in PTMC fine-needle aspiration (FNA) specimens has not been explored. This study aimed to evaluate the feasibility of WES using FNA specimens of PTMC. Five PTMC patients were enrolled with clinical characteristics gathered. Fine aspiration cytology needle (23 gauges) was used to collect FNA biopsy with ultrasound guidance. WES analysis of FNA specimens from five PTMC patients and matched blood samples was performed. The WES of FNA samples yielded an average sequencing depth of 281× and average coverage of 99.5%. We identified 534 somatic single-nucleotide variants and 13 indels in total, and per sample, we found a mean of 24 exonic mutations, which affected a total of 120 genes. In the PTMC FNA samples, the most frequently mutated genes were BRAF and ANKRD18B, and the four driver genes were BRAF, AFF3, SRCAP, and EGFR. We also identified several germline cancer predisposing gene mutations. The results suggest that WES of FNA specimens is feasible for PTMC and can identify novel genetic mutations.

Comprehensive Long-Read Sequencing Analysis Discloses the Transcriptome Features of Papillary Thyroid Microcarcinoma

CONTEXT

Papillary thyroid microcarcinoma (PTMC) is the most common type of thyroid cancer. It has been shown that lymph node metastasis is associated with poor prognosis in patients with PTMC.

OBJECTIVE

We aim to characterize the PTMC transcriptome landscape and identify the candidate transcripts that are associated with lateral neck lymph node metastasis of PTMC.

METHODS

We performed full-length transcriptome sequencing in 64 PTMC samples. Standard bioinformatic pipelines were applied to characterize and annotate the full-length expression profiles of 2 PTMC subtypes. Functional open reading frame (ORF) annotation of the known and novel transcripts were predicted by HMMER, DeepLoc, and DeepTMHMM tools. Candidate transcripts associated with the pN1b subtype were identified after transcript quantification and differential gene expression analyses.

RESULTS

We found that skipping exons accounted for the more than 27.82% of the alternative splicing events. At least 42.56% of the discovered transcripts were novel isoforms of annotated genes. A total of 39 193 ORFs in novel transcripts and 18 596 ORFs in known transcripts were identified. Distribution patterns of the characterized transcripts in functional domain, subcellular localization, and transmembrane structure were predicted. In total, 1033 and 1204 differentially expressed genes were identified in the pN0 and pN1b groups, respectively. Moreover, novel isoforms of FRMD3, NOD1, and SHROOM4 were highlighted for their association with pN1b subtype.

CONCLUSION

Our data provided the global transcriptome landscape of PTMC and also revealed the novel isoforms that associated with PTMC aggressiveness.

What can we learn about acid-base transporters in cancer from studying somatic mutations in their genes?

Acidosis is a chemical signature of the tumour microenvironment that challenges intracellular pH homeostasis. The orchestrated activity of acid-base transporters of the solute-linked carrier (SLC) family is critical for removing the end-products of fermentative metabolism (lactate/H+) and maintaining a favourably alkaline cytoplasm. Given the critical role of pH homeostasis in enabling cellular activities, mutations in relevant SLC genes may impact the oncogenic process, emerging as negatively or positively selected, or as driver or passenger mutations. To address this, we performed a pan-cancer analysis of The Cancer Genome Atlas simple nucleotide variation data for acid/base-transporting SLCs (ABT-SLCs). Somatic mutation patterns of monocarboxylate transporters (MCTs) were consistent with their proposed essentiality in facilitating lactate/H+ efflux. Among all cancers, tumours of uterine corpus endometrial cancer carried more ABT-SLC somatic mutations than expected from median tumour mutation burden. Among these, somatic mutations in SLC4A3 had features consistent with meaningful consequences on cellular fitness. Definitive evidence for ABT-SLCs as 'cancer essential' or 'driver genes' will have to consider microenvironmental context in genomic sequencing because bulk approaches are insensitive to pH heterogeneity within tumours. Moreover, genomic analyses must be validated with phenotypic outcomes (i.e. SLC-carried flux) to appreciate the opportunities for targeting acid-base transport in cancers.

Multi-omics analysis reveals a molecular landscape of the early recurrence and early metastasis in pan-cancer

Cancer remains a formidable challenge in medicine due to its propensity for recurrence and metastasis, which can result in unfavorable treatment outcomes. This challenge is particularly acute for early-stage patients, who may experience recurrence and metastasis without timely detection. Here, we first analyzed the differences in clinical characteristics among the primary tumor, recurrent tumor, and metastatic tumor in different stages of cancer, which may be caused by the molecular level. Moreover, the importance of predicting early cancer recurrence and metastasis is emphasized by survival analyses. Next, we used a multi-omics approach to identify key molecular changes associated with early cancer recurrence and metastasis and discovered that early metastasis in cancer demonstrated a high degree of genomic and cellular heterogeneity. We performed statistical comparisons for each level of omics data including gene expression, mutation, copy number variation, immune cell infiltration, and cell status. Then, various analytical techniques, such as proportional hazard model and Fisher's exact test, were used to identify specific genes or immune characteristics associated with early cancer recurrence and metastasis. For example, we observed that the overexpression of BPIFB1 and high initial B-cell infiltration levels are linked to early cancer recurrence, while the overexpression or amplification of ANKRD22 and LIPM, mutation of IGHA1 and MUC16, high fibroblast infiltration level, M1 polarization of macrophages, cellular status of DNA repair are all linked to early cancer metastasis. These findings have led us to construct classifiers, and the average area under the curve (AUC) of these classifiers was greater than 0.75 in The Cancer Genome Atlas (TCGA) cancer patients, confirming that the features we identified could be biomarkers for predicting recurrence and metastasis of early cancer. Finally, we identified specific early sensitive targets for targeted therapy and immune checkpoint inhibitor therapy. Once the biomarkers we identified changed, treatment-sensitive targets can be treated accordingly. Our study has comprehensively characterized the multi-omics characteristics and identified a panel of biomarkers of early cancer recurrence and metastasis. Overall, it provides a valuable resource for cancer recurrence and metastasis research and improves our understanding of the underlying mechanisms driving early cancer recurrence and metastasis.