Gene Mutations That Cause Disease

Types of Genetic Mutations and Their Functional Consequences

Mutations can be classified at multiple levels. At the nucleotide level: substitutions (missense, nonsense, or synonymous), insertions, and deletions, the latter two causing frameshifts when not in multiples of three. At the chromosomal level: amplifications (increased gene copy number), deletions (loss of chromosomal segments), and translocations (rearrangements between chromosomes).

The functional consequence depends on the location, not just the type. A missense mutation at KRAS codon 12 creates a constitutively active oncoprotein that locks KRAS in the GTP-bound state and drives constitutive BRAF/MEK/ERK and PI3K/AKT signalling. A missense mutation at TP53 R175H produces a stable but non-functional protein with dominant-negative effects. Context — evolutionary conservation, protein domain structure, and signalling network position — determines pathogenicity.

• ·Missense mutations: amino acid substitution — can activate oncogenes (KRAS G12D) or inactivate tumor suppressors (TP53 R175H)
• ·Nonsense mutations: premature stop codon — truncated protein, usually loss of function (common in APC, BRCA1)
• ·Frameshift insertions/deletions: altered reading frame downstream — typically loss of function (BRCA2 frameshift)
• ·Splice site mutations: aberrant splicing, exon skipping or intron retention — common in TP53, BRCA1
• ·Copy number amplifications: gene overexpression — HER2 amplification, EGFR amplification in GBM
• ·Gene fusions: chimeric oncoproteins — BCR-ABL in CML, EML4-ALK in NSCLC

Driver vs Passenger Mutations

A cancer cell's genome harbours thousands of mutations, but only a small fraction — driver mutations — provide selective growth advantage and are causally involved in oncogenesis. The remainder are passenger mutations, acquired during tumour evolution without functional consequence. Distinguishing drivers from passengers requires statistical analysis across large cancer cohorts, looking for mutation patterns that exceed background rates.

The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) have catalogued driver mutations across thousands of tumours. TP53 mutations occur far more often than expected by chance in ~50% of all cancers, firmly establishing it as a pan-cancer driver. KRAS codon 12 and 13 mutations cluster at specific positions — a hallmark of positive selection indicating these specific amino acid changes, not random mutation, drive cancer.

Germline vs Somatic Mutations

Germline mutations are inherited through the germ line, present in every cell of the organism from fertilisation. They underlie hereditary cancer syndromes — BRCA1/2 in hereditary breast and ovarian cancer, Lynch syndrome (MLH1, MSH2) in hereditary colorectal cancer, and TP53 in Li-Fraumeni syndrome. Germline carriers are detected through genetic testing and managed with surveillance and risk-reduction strategies.

Somatic mutations arise in individual cells after fertilisation, accumulating throughout life through replication errors, environmental mutagen exposure, and repair defects. They are present only in the mutated cell and its descendants — the tumour. Somatic mutation rate is ~1 mutation per cell division for base substitutions but varies enormously across cancer types: UV-damaged melanomas may carry 100,000+ mutations, while childhood acute leukaemias carry only dozens.

How Mutations Activate Oncogenes

Oncogene activation requires a gain-of-function mutation — the gene acquires a new or enhanced activity that promotes proliferation. The three major mechanisms are point mutations (KRAS G12C, BRAF V600E), amplification (MYC amplification in neuroblastoma, HER2 amplification in breast cancer), and chromosomal translocation creating fusion oncoproteins (BCR-ABL in CML, EML4-ALK in NSCLC).

BRAF V600E is a textbook example of a gain-of-function point mutation: the glutamate substitution mimics phosphorylation in the activation loop, constitutively activating the kinase without upstream RAS input. This single nucleotide change is sufficient to transform normal melanocytes into melanoma cells in experimental models.

Gene amplifications cause overexpression proportional to copy number. HER2 amplification produces 10–30-fold more receptor protein on the cell surface, creating constitutive receptor clustering and downstream signalling even at low ligand concentrations. The therapeutic window this creates — normal cells with 2 copies of HER2 vs tumour cells with 30+ copies — is exploited by trastuzumab and trastuzumab deruxtecan.

How Mutations Inactivate Tumor Suppressors

Tumor suppressor inactivation typically requires loss of function in both alleles. The most common mechanisms are point mutations generating truncated or non-functional proteins, deletions removing the gene entirely, and epigenetic silencing via promoter methylation — functionally equivalent to mutation but without DNA sequence change.

TP53 missense mutations are particularly complex: ~75% of cancer-associated TP53 mutations produce a full-length but conformationally altered protein. Many of these mutants not only lack wild-type p53 activity but exert dominant-negative effects on the remaining wild-type allele and gain new oncogenic functions — promoting invasion, chemotherapy resistance, and altered metabolism.

BRCA1 mutations illustrate the spectrum of loss-of-function mechanisms. Deleterious BRCA1 variants include frameshift mutations (most common), nonsense mutations, splice site mutations, and missense mutations affecting conserved BRCT or RING domains. Variants of uncertain significance (VUS) in BRCA1 represent a clinical challenge, requiring functional assays and co-segregation data to classify.

Clinical Implications: From Mutation to Treatment

Identifying driver mutations has transformed cancer treatment from empirical chemotherapy to biomarker-directed precision therapy. EGFR mutations predict EGFR inhibitor sensitivity; KRAS G12C is targeted by sotorasib; BRAF V600E by vemurafenib/dabrafenib; BCR-ABL by imatinib. The matching of specific mutations to specific drugs — rather than histology — defines modern oncology.

Beyond direct targeting, mutations inform resistance mechanisms and combination strategies. KRAS co-mutations predict resistance to EGFR inhibitors. RB1 loss predicts resistance to CDK4/6 inhibitors. Comprehensive genomic profiling of tumours — via next-generation sequencing — now guides treatment decisions across virtually every cancer type.

Germline testing has equal importance. BRCA1/2 testing guides PARP inhibitor use, risk-reduction surgery, and cascade testing of family members. Lynch syndrome testing in colorectal cancer identifies patients for immune checkpoint immunotherapy (high microsatellite instability predicts PD-1 blockade response) and family counselling.