Cancer Genetics and Somatic Variation

Q: What are the hallmarks of cancer?

The hallmarks of cancer are a small set of acquired capabilities that together define malignant transformation. The original six (Hanahan & Weinberg 2000, Cell 100:57) are sustained proliferative signalling, evasion of growth suppressors, resistance to cell death, replicative immortality, induced angiogenesis, and activated invasion / metastasis. The 2011 update added two enabling characteristics (genome instability and tumour-promoting inflammation) and two emerging hallmarks (deregulated metabolism and immune evasion). The 2022 update (Hanahan, Cancer Discovery 12:31) adds phenotypic plasticity, non-mutational epigenetic reprogramming, polymorphic microbiomes, and senescent cells as new hallmarks.

Short version. Cancer biology stands on three pillars: gain-of-function activation of proto-oncogenes; loss-of-function inactivation of tumour suppressors; and somatic genomic evolution under Darwinian selection. The hallmarks-of-cancer framework (Hanahan & Weinberg 2000, 2011, 2022) ties them to acquired capabilities; the Knudson two-hit hypothesis (Knudson 1971) connects germline predisposition to somatic biallelic loss; and the TCGA / ICGC / PCAWG datasets give the cross-cancer mutational landscape. Each pillar has its own page, linked below.

Educational positioning. Evagene is an academic, research, and educational pedigree modelling platform; it is not a medical device, not a diagnostic, and not a screening or decision-support tool. The risk models implemented (BayesMendel BRCAPRO, MMRpro, PancPRO; Tyrer-Cuzick IBIS-style approximation; Claus, Couch, Frank, Manchester, NICE; Gail; Amsterdam II / revised Bethesda; CanRisk export for off-platform BOADICEA) produce illustrative outputs for research and teaching only, not clinical recommendations. Where this page references published surveillance or testing guidelines, it does so neutrally — the published guidelines describe X, not the patient should X.

The three pillars at a glance

Cancer genetics is not a single field; it is the convergence of three. Understanding any specific tumour requires drawing on all three.

Oncogenes and tumour suppressors — the gene-level mechanisms by which mutation causes the cellular phenotype of cancer. Read about activation by point mutation, amplification, and translocation; the Knudson two-hit model for tumour-suppressor inactivation; the gatekeeper / caretaker / landscaper distinction; and the driver-versus-passenger problem in oncogenes and tumour suppressors.
Inherited cancer predisposition — the syndromes in which a germline pathogenic variant elevates lifetime cancer risk in defined organ systems. Read about HBOC, Lynch syndrome, FAP, MAP, Li-Fraumeni, Cowden, Peutz-Jeghers, juvenile polyposis, hereditary diffuse gastric cancer, von Hippel-Lindau, MEN1 and MEN2, NF1, NF2, tuberous sclerosis, and retinoblastoma in inherited cancer predisposition. The Evagene hereditary cancer risk assessment page covers the published risk-model algorithms relevant to these syndromes.
Somatic genomics — the molecular landscape of established tumours: clonal evolution, mutational signatures, tumour mutational burden, microsatellite instability, homologous-recombination deficiency, and the targeted-therapy biomarkers (HER2, BCR-ABL, BRAF V600E, KRAS G12C, MSI-H / dMMR, BRCA1/2 / HRD) that link genotype to therapeutic response. Read about clonal evolution, mutational signatures, and biomarker landscape in somatic genomics.

Foundational figures and frameworks

Five foundational pieces of work shape the way contemporary cancer genetics is taught and read. None is older than 1971; none is fully superseded.

Knudson's two-hit hypothesis (1971)

Reasoning from the bimodal age-of-onset distribution in retinoblastoma, Knudson 1971 (PNAS 68:820) proposed that the heritable form of the disease arises when an individual inherits one inactivating event at a tumour-suppressor locus — what would later be identified as RB1 — and acquires a second somatic event in a single retinal cell. The non-heritable form requires both events to be acquired somatically in the same cell, a much rarer occurrence. The two-hit model became the conceptual scaffold for tumour-suppressor genetics, was directly verified at the RB1 locus in the 1980s, and remains the framework used to interpret loss of heterozygosity (LOH) in tumour DNA today.

Bishop on cellular oncogenes (1991)

The discovery that the transforming sequences in acutely transforming retroviruses derive from cellular genes — that the v-src of Rous sarcoma virus has a cellular homologue c-src — reframed the oncogene from a viral peculiarity to a normal cellular gene whose dysregulation drives malignancy. Mike Bishop's review Bishop 1991 (Cell 64:235) consolidated this picture, anchored the concept of the proto-oncogene, and set up the next two decades of work on RAS, MYC, ERBB2 / HER2, EGFR, BRAF, and the rest of the canonical oncogene catalogue.

Hanahan and Weinberg's hallmarks of cancer (2000, 2011, 2022)

Hanahan & Weinberg 2000 (Cell 100:57) proposed that the genotypic complexity of cancer collapses to a small set of acquired capabilities: sustained proliferative signalling, evasion of growth suppressors, resistance to cell death, replicative immortality, induced angiogenesis, and activated invasion and metastasis. The 2011 update Hanahan & Weinberg 2011 (Cell 144:646) added genome instability and tumour-promoting inflammation as enabling characteristics, and deregulated cellular energetics and immune evasion as emerging hallmarks. The 2022 update Hanahan 2022 (Cancer Discovery 12:31) adds phenotypic plasticity, non-mutational epigenetic reprogramming, polymorphic microbiomes, and senescent cells as further hallmarks. The framework is the standard organising principle for graduate-level oncology teaching and for translational drug-discovery programmes alike.

Vogelstein, Kinzler, and the cancer-genome landscape (2013)

Vogelstein et al. 2013 (Science 339:1546) synthesised a decade of large-scale tumour-sequencing studies into a working model of the cancer genome: a small number of driver mutations in a curated set of ~140 cancer genes, recurrent across tumour types, plus a long tail of passenger mutations that contribute nothing to the malignant phenotype. The earlier Kinzler & Vogelstein 1997 (Nature 386:761) distinction between gatekeeper genes (which directly restrain growth) and caretaker genes (which maintain genome stability) survives as part of the standard taxonomy.

The Cancer Genome Atlas and the Pan-Cancer Analysis of Whole Genomes

The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium / Pan-Cancer Analysis of Whole Genomes (ICGC/TCGA PCAWG Consortium 2020, Nature 578:82) collectively sequenced tens of thousands of tumours across dozens of organ systems. The result is the empirical mutational landscape that anchors contemporary cancer genomics: per-tumour-type driver-gene catalogues, mutational-signature decompositions, structural-variant typologies, and the cross-tissue comparisons that ground statements such as "BRAF V600E is the dominant driver in cutaneous melanoma" or "TP53 is mutated in roughly half of all sequenced solid tumours". The PCAWG companion paper on signatures (Alexandrov et al. 2020, Nature 578:94) is covered in detail on the somatic genomics page.

Germline meets somatic

The cleanest illustration of how the germline and somatic worlds intersect is the inherited cancer-predisposition syndromes. In a BRCA1-associated breast cancer, the germline pathogenic BRCA1 variant supplies one inactivating allele in every cell of the body, including every breast epithelial cell. The second allele is lost somatically in the cell of origin — typically by loss of heterozygosity, sometimes by point mutation or epigenetic silencing. The resulting cell now lacks functional BRCA1, is homologous-recombination deficient, accumulates the kind of structural-variant burden captured by mutational signature 3, and is selectively sensitive to PARP inhibition. The germline event without the somatic event yields a phenotypically normal cell; the somatic event alone in a non-carrier yields the same phenotype but at much lower per-cell rates, hence the population frequency difference between hereditary and sporadic disease.

The same template applies to RB1 in retinoblastoma, MLH1 / MSH2 / MSH6 / PMS2 in Lynch-syndrome colorectal and endometrial cancer (where the somatic second hit produces the microsatellite instability seen by IHC and MSI testing), APC in FAP-associated colorectal cancer, TP53 in Li-Fraumeni-spectrum tumours, and most other dominantly-inherited cancer-predisposition genes. The pedigree captures the germline; the tumour molecular profile captures the somatic. Both are needed to reason about a family.

What Evagene contributes (and what it does not)

Evagene's contribution sits cleanly in the family-history / pedigree-modelling layer:

Pedigree drawing with NSGC-standard notation, GEDCOM and CanRisk export, and a 1,900-entry help catalogue. See pedigree drawing tool.
Implementations of published cancer-risk algorithms — BayesMendel BRCAPRO, MMRpro, PancPRO; breast cancer family-history scoring; ovarian cancer family-history scoring; pancreatic cancer family history; Lynch-syndrome family-history scoring; Tyrer-Cuzick (IBIS-style approximation, not the official IBIS Breast Cancer Risk Evaluator binary); Gail NCI BCRAT; Manchester scoring; NICE CG164 / NG101 family-history triage representation; Amsterdam II / revised Bethesda criteria representation.
CanRisk file export for off-platform BOADICEA computation. BOADICEA is licensed by the University of Cambridge and is not bundled in Evagene; Evagene exports a ##CanRisk 2.0 pedigree file that the user uploads at canrisk.org. Versioning caveat: CanRisk v3 (released 2025), with BOADICEA breast cancer v7 and ovarian v3, introduced UK-ethnicity-specific parameters, Volpara / Stratus mammographic density, and pre-menopause-status fields that the v2.0 export does not carry; for those v3 fields, enter the family directly at canrisk.org. See BOADICEA vs BRCAPRO for the architectural rationale.

Evagene does not compute somatic-tumour mutational signatures, perform variant-classification against ClinVar, or run tumour-genomic interpretation. It is a research and teaching tool, not a diagnostic or decision-support platform. The somatic-genomics content on this site is educational reference. Where this page or its sub-topics describe a published surveillance protocol or guideline (NCCN, ESMO, EHTG, NICE), the framing is consistently the guideline describes X, not the patient should X; Evagene does not issue surveillance, screening, or testing recommendations.

How to read the rest of the pillar

The three sub-topic pages can be read in order or independently:

Oncogenes and tumour suppressors — mechanisms of activation and inactivation; canonical examples (RAS family, MYC, BCR-ABL1, ERBB2 / HER2, EGFR, BRAF, RB1, TP53, APC, BRCA1 / BRCA2, PTEN, CDKN2A, the MMR genes, STK11, NF1, NF2, VHL); haploinsufficiency; gatekeeper / caretaker / landscaper; driver versus passenger.
Inherited cancer predisposition — HBOC, Lynch, FAP, MAP, Li-Fraumeni, Cowden, Peutz-Jeghers, juvenile polyposis, HDGC, VHL, MEN1 and MEN2, NF1, NF2, tuberous sclerosis, retinoblastoma; lifetime risk estimates from the published cohorts; how the published guidelines describe surveillance for each.
Somatic genomics — clonal evolution, multi-region sequencing and tumour phylogenetics, ctDNA, CHIP, mutational signatures (SBS / DBS / ID), HRD scoring, MSI, TMB, and the targeted-therapy biomarker landscape.

Selected sources

Knudson AG. Mutation and cancer: statistical study of retinoblastoma. PNAS 1971; 68:820. PMID 5279523.
Bishop JM. Molecular themes in oncogenesis. Cell 1991; 64:235. PMID 1988146.
Kinzler KW, Vogelstein B. Gatekeepers and caretakers. Nature 1997; 386:761. PMID 9126724.
Hanahan D, Weinberg RA. The hallmarks of cancer. Cell 2000; 100:57. PMID 10647931.
Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell 2011; 144:646. PMID 21376230.
Hanahan D. Hallmarks of cancer: new dimensions. Cancer Discovery 2022; 12:31. PMID 35022204.
Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA, Kinzler KW. Cancer genome landscapes. Science 2013; 339:1546. PMID 23539594.
ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature 2020; 578:82. PMID 32025007.
The Cancer Genome Atlas Program. cancer.gov/tcga.

Frequently asked questions

What is the relationship between germline and somatic mutation in cancer?

Germline variants are inherited and present in every nucleated cell, shaping lifetime susceptibility but rarely sufficient on their own. Somatic mutations are acquired in tumour-precursor cell lineages and are the proximate genetic cause of malignancy. In hereditary cancer, the germline variant typically supplies one inactivating event in a tumour suppressor (per Knudson 1971) and a second somatic event completes biallelic loss in the cell of origin.

What are the hallmarks of cancer?

Acquired capabilities defining malignant transformation: the original six (Hanahan & Weinberg 2000) plus genome instability and tumour-promoting inflammation as enabling characteristics (2011) and phenotypic plasticity, non-mutational epigenetic reprogramming, polymorphic microbiomes, and senescent cells in the 2022 update.

Oncogene versus tumour suppressor — what is the difference?

An oncogene is the activated, gain-of-function form of a normal cellular gene; it is dominant at the cellular level. A tumour suppressor restrains proliferation, maintains genome integrity, or promotes apoptosis; tumour suppressors are typically recessive, requiring biallelic inactivation per Knudson's two-hit model.

Does Evagene compute somatic-tumour mutational signatures?

No. Evagene is an academic, research, and educational pedigree modelling platform. It documents family history, applies published risk-model algorithms (BRCAPRO, MMRpro, PancPRO, Tyrer-Cuzick IBIS-style approximation, Claus, Couch, Frank, Manchester, NICE, Gail, Amsterdam II / revised Bethesda) and exports CanRisk pedigree files for off-platform BOADICEA. Somatic-genomics content here is educational reference, not platform output.