Spatiotemporal assessment of immunogenomic heterogeneity in multiple myeloma.

Spatial heterogeneity is a common phenomenon in metastatic solid tumors and an evolving concept in multiple myeloma (MM). The interplay between malignant plasma cells (PCs) and the microenvironment has not yet been analyzed in MM. For this purpose, we performed bone marrow aspirates and imaging-guided biopsies of corresponding lesions in newly diagnosed MM (NDMM) and relapsed/refractory MM (RRMM) patients. PCs were isolated and subjected to whole-exome sequencing (WES). Non-PCs were studied with next-generation flow (NGF) and T-cell receptor sequencing (TCRseq) to analyze the connection between malignant and nonmalignant cells in the bone marrow and in lesions. Although we observed a strong overlap from WES, NGF, and TCRseq in patients with intramedullary disease, WES revealed significant spatial heterogeneity in patients with extramedullary disease. NGF showed significant immunosuppression in RRMM compared with NDMM as indicated by fewer myeloid dendritic cells, unswitched memory B cells, Th9 cells, and CD8 effector memory T cells but more natural killer and regulatory T cells. Additionally, fewer T-cell receptor (TCR) sequences were detected in RRMM compared with NDMM and healthy individuals. After induction therapy, TCR repertoire richness increased to levels of healthy individuals, and NGF showed more regulatory T cells and myeloid-derived suppressor cells, regardless of depth of response. Clinical significance of imaging-guided biopsies of lesions was demonstrated by detection of monoclonal PCs in patients without measurable residual disease (MRD) in aspirates from the iliac crest as well as identification of secondary primary malignancies in MRD- patients. Furthermore, site-specific clones with different drug susceptibilities and genetically defined high-risk features were detected by our workflow.

Deciphering spatial genomic heterogeneity at a single cell resolution in multiple myeloma.

Osteolytic lesions (OL) characterize symptomatic multiple myeloma. The mechanisms of how malignant plasma cells (PC) cause OL in one region while others show no signs of bone destruction despite subtotal infiltration remain unknown. We report on a single-cell RNA sequencing (scRNA-seq) study of PC obtained prospectively from random bone marrow aspirates (BM) and paired imaging-guided biopsies of OL. We analyze 148,630 PC from 24 different locations in 10 patients and observe vast inter- and intra-patient heterogeneity based on scRNA-seq analyses. Beyond the limited evidence for spatial heterogeneity from whole-exome sequencing, we find an additional layer of complexity by integrated analysis of anchored scRNA-seq datasets from the BM and OL. PC from OL are characterized by differentially expressed genes compared to PC from BM, including upregulation of genes associated with myeloma bone disease like DKK1, HGF and TIMP-1 as well as recurrent downregulation of JUN/FOS, DUSP1 and HBB. Assessment of PC from longitudinally collected samples reveals transcriptional changes after induction therapy. Our study contributes to the understanding of destructive myeloma bone disease.

An adaptive method of defining negative mutation status for multi-sample comparison using next-generation sequencing.

BACKGROUND: Multi-sample comparison is commonly used in cancer genomics studies. By using next-generation sequencing (NGS), a mutation's status in a specific sample can be measured by the number of reads supporting mutant or wildtype alleles. When no mutant reads are detected, it could represent either a true negative mutation status or a false negative due to an insufficient number of reads, so-called "coverage". To minimize the chance of false-negative, we should consider the mutation status as "unknown" instead of "negative" when the coverage is inadequately low. There is no established method for determining the coverage threshold between negative and unknown statuses. A common solution is to apply a universal minimum coverage (UMC). However, this method relies on an arbitrarily chosen threshold, and it does not take into account the mutations' relative abundances, which can vary dramatically by the type of mutations. The result could be misclassification between negative and unknown statuses. METHODS: We propose an adaptive mutation-specific negative (MSN) method to improve the discrimination between negative and unknown mutation statuses. For a specific mutation, a non-positive sample is compared with every known positive sample to test the null hypothesis that they may contain the same frequency of mutant reads. The non-positive sample can only be claimed as "negative" when this null hypothesis is rejected with all known positive samples; otherwise, the status would be "unknown". RESULTS: We first compared the performance of MSN and UMC methods in a simulated dataset containing varying tumor cell fractions. Only the MSN methods appropriately assigned negative statuses for samples with both high- and low-tumor cell fractions. When evaluated on a real dual-platform single-cell sequencing dataset, the MSN method not only provided more accurate assessments of negative statuses but also yielded three times more available data after excluding the "unknown" statuses, compared with the UMC method. CONCLUSIONS: We developed a new adaptive method for distinguishing unknown from negative statuses in multi-sample comparison NGS data. The method can provide more accurate negative statuses than the conventional UMC method and generate a remarkably higher amount of available data by reducing unnecessary "unknown" calls.

Ultradeep sequencing differentiates patterns of skin clonal mutations associated with sun-exposure status and skin cancer burden.

In ultraviolet (UV) radiation-exposed skin, mutations fuel clonal cell growth. The relationship between UV exposure and the accumulation of clonal mutations (CMs) and the correlation between CMs and skin cancer risk are largely unexplored. We characterized 450 individual-matched sun-exposed (SE) and non-SE (NE) normal human skin samples. The number and relative contribution of CMs were significantly different between SE and NE areas. Furthermore, we identified hotspots in TP53, NOTCH1, and GRM3 where mutations were significantly associated with UV exposure. In the normal skin from patients with cutaneous squamous cell carcinoma, we found that the cancer burden was associated with the UV-induced mutations, with the difference mostly conferred by the low-frequency CMs. These findings provide previously unknown information on UV's carcinogenic effect and pave the road for future development of quantitative assessment of subclinical UV damage and skin cancer risk.

Complete response to anti-PD-L1 antibody in a metastatic bladder cancer associated with novel MSH4 mutation and microsatellite instability.

BACKGROUND: Microsatellite instability (MSI) occurs in 3% of urothelial carcinomas as a result of germline or somatic loss of function mutation in mismatch repair (MMR) proteins.1 Although MSH4 is a member of the DNA MMR mutS family, the association of MSH4 mutation with MSI has not been described. We report a complete responder to PD-L1 blockade who had MSH4 mutated metastatic bladder cancer with mixed histology and MSI. The genomics of urothelial, plasmacytoid and squamous histology was characterized individually through microdissection. CASE PRESENTATION: An 81-year-old man was diagnosed with metastatic urothelial carcinoma 8 months after a cystectomy for muscle invasive bladder cancer. His disease was primary refractory to first-line platinum-based chemotherapy but attained complete response to second-line atezolizumab. PCR-based assay revealed MSI high. The tumor mutational burden was elevated to 36.7 mut/Mb. However, immunohistochemistry of MLH1, MSH2, MSH6 and PMS2 was intact. Whole exome sequencing confirmed that the above mentioned four classic MMR genes were wild type but revealed a deleterious MSH4 L359I mutation with variant allele fraction of 30% and Polyphen2 score of 0.873. The association of MSH4 alterations and MSI-H was independently verified in two publicly available MSI-H colorectal cancer datasets. CONCLUSIONS: The novel MSH4 L359I mutation is associated with MSI and high mutational burden leading to remarkable response to PD-L1 blockade. More studies are warranted to establish the causality relationship between MSH4 and MSI.