The Ecology and Evolution of Cancer: The Ultra-Microevolutionary Process.

Although tumorigenesis has been accepted as an evolutionary process ( 20 , 102 ), many forces may operate differently in cancers than in organisms, as they evolve at vastly different time scales. Among such forces, natural selection, here defined as differential cellular proliferation among distinct somatic cell genotypes, is particularly interesting because its action might be thwarted in multicellular organisms ( 20 , 29 ). In this review, selection is analyzed in two stages of cancer evolution: Stage I is the evolution between tumors and normal tissues, and Stage II is the evolution within tumors. The Cancer Genome Atlas (TCGA) data show a low degree of convergent evolution in Stage I, where genetic changes are not extensively shared among cases. An equally important, albeit much less highlighted, discovery using TCGA data is that there is almost no net selection in cancer evolution. Both positive and negative selection are evident but they neatly cancel each other out, rendering total selection ineffective in the absence of recombination. The efficacy of selection is even lower in Stage II, where neutral (non-Darwinian) evolution is increasingly supported by high-density sampling studies ( 81 , 123 ). Because natural selection is not a strong deterministic force, cancers usually evolve divergently even in similar tissue environments.

Artificial intelligence-assisted system for precision diagnosis of PD-L1 expression in non-small cell lung cancer.

Standardized programmed death-ligand 1 (PD-L1) assessment in non-small cell lung cancer (NSCLC) is challenging, owing to inter-observer variability among pathologists and the use of different antibodies. There is a strong demand for the development of an artificial intelligence (AI) system to obtain high-precision scores of PD-L1 expression in clinical diagnostic scenarios. We developed an AI system using whole slide images (WSIs) of the 22c3 assay to automatically assess the tumor proportion score (TPS) of PD-L1 expression based on a deep learning (DL) model of tumor detection. Tests were performed to show the diagnostic ability of the AI system in the 22c3 assay to assist pathologists and the reliability of the application in the SP263 assay. A robust high-performance DL model for automated tumor detection was devised with an accuracy and specificity of 0.9326 and 0.9641, respectively, and a concrete TPS value was obtained after tumor cell segmentation. The TPS comparison test in the 22c3 assay showed strong consistency between the TPS calculated with the AI system and trained pathologists (R = 0.9429-0.9458). AI-assisted diagnosis test confirmed that the repeatability and efficiency of untrained pathologists could be improved using the AI system. The Ventana PD-L1 (SP263) assay showed high consistency in TPS calculations between the AI system and pathologists (R = 0.9787). In conclusion, a high-precision AI system is proposed for the automated TPS assessment of PD-L1 expression in the 22c3 and SP263 assays in NSCLC. Our study also indicates the benefits of using an AI-assisted system to improve diagnostic repeatability and efficiency for pathologists.

Exome sequencing reveals the genetic landscape and frequent inactivation of PCDHB3 in Chinese rectal cancers.

Colorectal cancer (CRC) is the third most common cancer worldwide, with more than 1.3 million new cases and 690 000 deaths each year. In China, the incidence of CRC has increased dramatically due to dietary and lifestyle changes, to become the fifth leading cause of cancer-related death. Here, we performed whole-exome sequencing in 50 rectal cancer cases among the Chinese population as part of the International Cancer Genome Consortium research project. Frequently mutated genes and enriched pathways were identified. Moreover, a previously unreported gene, PCDHB3, was found frequently mutated in 5.19% cases. Additionally, PCDHB3 expression was found decreased in 81.6% of CRC tissues and all eight CRC cell lines tested. Low expression and cytoplasmic localization of PCDHB3 predict poor prognosis in advanced CRC. Copy number decrease and/or CpG island hypermethylation contributes to the pervasive decreased expression of PCDHB3. PCDHB3 inhibits CRC cell proliferation, migration, and epithelial-mesenchymal transition. The tumor-suppressive effects of PCDHB3 are partially due to inhibition of NF-κB transcriptional activity through K63 deubiquitination of p50 at lysine 244/252, which increases the binding affinity of inactive p50 homodimer to κB DNA, resulting in competitive inhibition of the transcription of NF-κB target genes by p65 dimers. Our study identified PCDHB3 as a novel tumor suppressor in CRC via inhibition of the NF-κB pathway, and its expression and localization may serve as prognostic markers for advanced CRC. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution.

The prevailing view that the evolution of cells in a tumor is driven by Darwinian selection has never been rigorously tested. Because selection greatly affects the level of intratumor genetic diversity, it is important to assess whether intratumor evolution follows the Darwinian or the non-Darwinian mode of evolution. To provide the statistical power, many regions in a single tumor need to be sampled and analyzed much more extensively than has been attempted in previous intratumor studies. Here, from a hepatocellular carcinoma (HCC) tumor, we evaluated multiregional samples from the tumor, using either whole-exome sequencing (WES) (n = 23 samples) or genotyping (n = 286) under both the infinite-site and infinite-allele models of population genetics. In addition to the many single-nucleotide variations (SNVs) present in all samples, there were 35 "polymorphic" SNVs among samples. High genetic diversity was evident as the 23 WES samples defined 20 unique cell clones. With all 286 samples genotyped, clonal diversity agreed well with the non-Darwinian model with no evidence of positive Darwinian selection. Under the non-Darwinian model, MALL (the number of coding region mutations in the entire tumor) was estimated to be greater than 100 million in this tumor. DNA sequences reveal local diversities in small patches of cells and validate the estimation. In contrast, the genetic diversity under a Darwinian model would generally be orders of magnitude smaller. Because the level of genetic diversity will have implications on therapeutic resistance, non-Darwinian evolution should be heeded in cancer treatments even for microscopic tumors.

Rapid growth of a hepatocellular carcinoma and the driving mutations revealed by cell-population genetic analysis of whole-genome data.

We present the analysis of the evolution of tumors in a case of hepatocellular carcinoma. This case is particularly informative about cancer growth dynamics and the underlying driving mutations. We sampled nine different sections from three tumors and seven more sections from the adjacent nontumor tissues. Selected sections were subjected to exon as well as whole-genome sequencing. Putative somatic mutations were then individually validated across all 9 tumor and 7 nontumor sections. Among the mutations validated, 24 were amino acid changes; in addition, 22 large indels/copy number variants (>1 Mb) were detected. These somatic mutations define four evolutionary lineages among tumor cells. Separate evolution and expansion of these lineages were recent and rapid, each apparently having only one lineage-specific protein-coding mutation. Hence, by using a cell-population genetic definition, this approach identified three coding changes (CCNG1, P62, and an indel/fusion gene) as tumor driver mutations. These three mutations, affecting cell cycle control and apoptosis, are functionally distinct from mutations that accumulated earlier, many of which are involved in inflammation/immunity or cell anchoring. These distinct functions of mutations at different stages may reflect the genetic interactions underlying tumor growth.

Estimating DNA polymorphism from next generation sequencing data with high error rate by dual sequencing applications.

BACKGROUND: As the error rate is high and the distribution of errors across sites is non-uniform in next generation sequencing (NGS) data, it has been a challenge to estimate DNA polymorphism (θ) accurately from NGS data. RESULTS: By computer simulations, we compare the two methods of data acquisition - sequencing each diploid individual separately and sequencing the pooled sample. Under the current NGS error rate, sequencing each individual separately offers little advantage unless the coverage per individual is high (>20X). We hence propose a new method for estimating θ from pooled samples that have been subjected to two separate rounds of DNA sequencing. Since errors from the two sequencing applications are usually non-overlapping, it is possible to separate low frequency polymorphisms from sequencing errors. Simulation results show that the dual applications method is reliable even when the error rate is high and θ is low. CONCLUSIONS: In studies of natural populations where the sequencing coverage is usually modest (~2X per individual), the dual applications method on pooled samples should be a reasonable choice.

Population genetics in nonmodel organisms: II. natural selection in marginal habitats revealed by deep sequencing on dual platforms.

Population genetics of species living in marginal habitats could be particularly informative about the genetics of adaptation, but such analyses have not been readily feasible until recently. Sonneratia alba, a mangrove species widely distributed in the Indo-West Pacific, provides a very suitable system for the study of local adaptation. In this study, we analyzed DNA variation by pooling 71 genes from 85-100 individuals for DNA sequencing. For each of the two nearby S. alba populations, we obtained ~2,500 × coverage on the Illumina GA platform and for the Sanya population, an additional 5,400 × coverage on the AB SOLiD platform. For the Sanya sample, although each sequencing method called many putative single nucleotide polymorphisms, the two sets of calls did not overlap, suggesting platform-dependent errors. Conventional sequencing corroborated that each population is monomorphic. The two populations differ by 54 bp of 79,000 sites, but 90% of the variants are found in 10% of the genes. Strong local adaptation and high migration may help to explain the extensive monomorphism shared by the two populations in the presence of a small number of highly differentiated loci.

Characterization of the complete chloroplast genome of Clematis orientalis (Ranunculaceae).

The medicinal plant Clematis orientalis L. belongs to the family Ranunculaceae. In this study, we determined the complete chloroplast genome sequence of C. orientalis and its phylogenetic relationships with other species. The complete chloroplast genome of C. glauca is 159,518 bp in length, circular in structure, and has four regions including a large single-copy (LSC) region of 79,453 bp; a small single-copy (SSC) region of 17,997 bp; and two inverted repeat (IR) regions of 31,034 bp. The GC content of the genome is 38%, and those of LSC, SSC, and IR regions are 36.2, 31.4, and 42%, respectively. The genome encodes 129 unique genes, including 85 protein-coding genes, 36 tRNA genes, and eight rRNA genes. Phylogenomic analysis reveals that C. orientalis is most closely related to C. aethusifolia. This study contributes to better understanding of phylogenetic relationships of Ranunculaceae.

Human papillomavirus integration perspective in small cell cervical carcinoma.

Small cell cervical carcinoma (SCCC) is a rare but aggressive malignancy. Here, we report human papillomavirus features and genomic landscape in SCCC via high-throughput HPV captured sequencing, whole-genome sequencing, whole-transcriptome sequencing, and OncoScan microarrays. HPV18 infections and integrations are commonly detected. Besides MYC family genes (37.9%), we identify SOX (8.4%), NR4A (6.3%), ANKRD (7.4%), and CEA (3.2%) family genes as HPV-integrated hotspots. We construct the genomic local haplotype around HPV-integrated sites, and find tandem duplications and amplified HPV long control regions (LCR). We propose three prominent HPV integration patterns: duplicating oncogenes (MYCN, MYC, and NR4A2), forming fusions (FGFR3-TACC3 and ANKRD12-NDUFV2), and activating genes (MYC) via the cis-regulations of viral LCRs. Moreover, focal CNA amplification peaks harbor canonical cancer genes including the HPV-integrated hotspots within MYC family, SOX2, and others. Our findings may provide potential molecular criteria for the accurate diagnosis and efficacious therapies for this lethal disease.

A standardized pathological proposal for evaluating microvascular invasion of hepatocellular carcinoma: a multicenter study by LCPGC.

BACKGROUND AND AIMS: Microvascular invasion (MVI) is a key pathological factor that severely affects the postoperative prognosis of patients with hepatocellular carcinoma (HCC). However, no MVI classification schemes based on standardized gross sampling protocols of HCC are available at present. METHODS: 119 HCC specimens were sampled at multiple sites (3-, 7-, and 13 points) for the optimum MVI detection rate. 16,144 resected HCCs were graded as M0, M1 or M2 by adopting three-tiered MVI grading (MVI-TTG) scheme based on the seven-point sampling protocol (SPSP). Survival analyses were performed on 2573 patients to explore the advantages of MVI-TTG. RESULTS: The MVI detection rate determined by SPSP was significantly higher than that determined by the 3-point sampling method (34.5% vs. 47.1%, p = 0.048), but was similar to that determined by the 13-point sampling method (47.1% vs. 51.3%, p = 0.517). Among 16,144 resected HCCs, the proportions of M0, M1 and M2 specimens according to SPSP were 53.4%, 26.2% and 20.4%, respectively. Postoperative survival analysis in 2573 HCC patients showed that the 3-year recurrence rates in M0, M1 and M2 MVI groups were 62.5%, 71.6% and 86.1%, respectively (p < 0.001), and the corresponding 3-year overall survival (OS) rates were 94.1%, 87.5% and 67.0%, respectively (p < 0.001). M1 grade was associated with early recurrence, while M2 grade was associated with both early and late recurrence. MVI-TTG had a larger area under the curve and net benefit rate than the two-tiered MVI grading scheme for predicting time to recurrence and OS. CONCLUSIONS: SPSP is a practical method to balance the efficacy of sampling numbers and MVI detection rates. MVI-TTG based on SPSP is a better prognostic predictor than the two-tiered MVI scheme. The combined use of SPSP and MVI-TTG is recommended for the routine pathological diagnosis of HCC.

KemaDom: a web server for domain prediction using kernel machine with local context.

Predicting domains of proteins is an important and challenging problem in computational biology because of its significant role in understanding the complexity of proteomes. Although many template-based prediction servers have been developed, ab initio methods should be designed and further improved to be the complementarity of the template-based methods. In this paper, we present a novel domain prediction system KemaDom by ensembling three kernel machines with the local context information among neighboring amino acids. KemaDom, an alternative ab initio predictor, can achieve high performance in predicting the number of domains in proteins. It is freely accessible at http://www.iipl.fudan.edu.cn/lschen/kemadom.htm and http://www.iipl.fudan.edu.cn/~lschen/kemadom.htm.

Integrated genomic analysis identifies deregulated JAK/STAT-MYC-biosynthesis axis in aggressive NK-cell leukemia.

Aggressive NK-cell leukemia (ANKL) is a rare form of NK cell neoplasm that is more prevalent among people from Asia and Central and South America. Patients usually die within days to months, even after receiving prompt therapeutic management. Here we performed the first comprehensive study of ANKL by integrating whole genome, transcriptome and targeted sequencing, cytokine array as well as functional assays. Mutations in the JAK-STAT pathway were identified in 48% (14/29) of ANKL patients, while the extracellular STAT3 stimulator IL10 was elevated by an average of 56-fold (P < 0.0001) in the plasma of all patients examined. Additional frequently mutated genes included TP53 (34%), TET2 (28%), CREBBP (21%) and MLL2 (21%). Patient NK leukemia cells showed prominent activation of STAT3 phosphorylation, MYC expression and transcriptional activities in multiple metabolic pathways. Functionally, STAT3 activation and MYC expression were critical for the proliferation and survival of ANKL cells. STAT signaling regulated the MYC transcription program, and both STAT signaling and MYC transcription were required to maintain the activation of nucleotide synthesis and glycolysis. Collectively, the JAK-STAT pathway represents a major target for genomic alterations and IL10 stimulation in ANKL. This newly discovered JAK/STAT-MYC-biosynthesis axis may provide opportunities for the development of novel therapeutic strategies in treating this subtype of leukemia.

Mutations or copy number losses of CD58 and TP53 genes in diffuse large B cell lymphoma are independent unfavorable prognostic factors.

The advent of next generation sequencing (NGS) technologies has expedited the discovery of novel genetic lesions in DLBCL. The prognostic significance of these identified gene mutations is largely unknown. In this study, we performed NGS for the 27 genes most frequently implicated in 196 patients. Interestingly, TP53 mutations were found to be significantly more common in DLBCL with MYC translocations (r = 0.446, P = 0.034). While no gene mutation was found to be more prevalent in patients with DLBCL with bone marrow involvement, MYD88 mutations were more common in primary DLBCL of the CNS or testis. To evaluate the prognostic significance of the abnormalities of these 27 genes, a total of 165 patients with newly diagnosed DLBCL, NOS were included in a multivariate survival analysis. Surprisingly, in addition to the TP53 mutation, CD58 mutation was found to predict poor clinical outcome. Furthermore, copy number loss of CD58 or TP53 was also identified to be an independent negative prognostic factor. Our results have uncovered the previously unknown critical impact of gene mutations on the prognosis of DLBCL and are fundamentally important for the future design of tailored therapy for improved clinical outcomes.

Identification of functional cooperative mutations of SETD2 in human acute leukemia.

Acute leukemia characterized by chromosomal rearrangements requires additional molecular disruptions to develop into full-blown malignancy, yet the cooperative mechanisms remain elusive. Using whole-genome sequencing of a pair of monozygotic twins discordant for MLL (also called KMT2A) gene-rearranged leukemia, we identified a transforming MLL-NRIP3 fusion gene and biallelic mutations in SETD2 (encoding a histone H3K36 methyltransferase). Moreover, loss-of-function point mutations in SETD2 were recurrent (6.2%) in 241 patients with acute leukemia and were associated with multiple major chromosomal aberrations. We observed a global loss of H3K36 trimethylation (H3K36me3) in leukemic blasts with mutations in SETD2. In the presence of a genetic lesion, downregulation of SETD2 contributed to both initiation and progression during leukemia development by promoting the self-renewal potential of leukemia stem cells. Therefore, our study provides compelling evidence for SETD2 as a new tumor suppressor. Disruption of the SETD2-H3K36me3 pathway is a distinct epigenetic mechanism for leukemia development.