Pushing the Frontiers of Cancer Research: Highlights from the Frontiers in Cancer Science Conference 2023.

The 15th annual Frontiers in Cancer Science (FCS) conference gathered scientific experts who shared the latest research converging upon several themes of cancer biology. These themes included the dysregulation of metabolism, cell death, and other signaling processes in cancer cells; using patient "omics" datasets and single-cell and spatial approaches to investigate heterogeneity, understand therapy resistance, and identify targets; innovative strategies for inhibiting tumors, including rational drug combinations and improved drug delivery mechanisms; and advances in models that can facilitate screening for cancer vulnerabilities and drug testing. We hope the insights from this meeting will stimulate further progress in the field.

Complete characterization of RNA biomarker fingerprints using a multi-modal ATR-FTIR and SERS approach for label-free early breast cancer diagnosis.

Breast cancer is a prevalent form of cancer worldwide, and the current standard screening method, mammography, often requires invasive biopsy procedures for further assessment. Recent research has explored microRNAs (miRNAs) in circulating blood as potential biomarkers for early breast cancer diagnosis. In this study, we employed a multi-modal spectroscopy approach, combining attenuated total reflection Fourier transform infrared (ATR-FTIR) and surface-enhanced Raman scattering (SERS) to comprehensively characterize the full-spectrum fingerprints of RNA biomarkers in the blood serum of breast cancer patients. The sensitivity of conventional FTIR and Raman spectroscopy was enhanced by ATR-FTIR and SERS through the utilization of a diamond ATR crystal and silver-coated silicon nanopillars, respectively. Moreover, a wider measurement wavelength range was achieved with the multi-modal approach than with a single spectroscopic method alone. We have shown the results on 91 clinical samples, which comprised 44 malignant and 47 benign cases. Principal component analysis (PCA) was performed on the ATR-FTIR, SERS, and multi-modal data. From the peak analysis, we gained insights into biomolecular absorption and scattering-related features, which aid in the differentiation of malignant and benign samples. Applying 32 machine learning algorithms to the PCA results, we identified key molecular fingerprints and demonstrated that the multi-modal approach outperforms individual techniques, achieving higher average validation accuracy (95.1%), blind test accuracy (91.6%), specificity (94.7%), sensitivity (95.5%), and F-score (94.8%). The support vector machine (SVM) model showed the best area under the curve (AUC) characterization value of 0.9979, indicating excellent performance. These findings highlight the potential of the multi-modal spectroscopy approach as an accurate, reliable, and rapid method for distinguishing between malignant and benign breast tumors in women. Such a label-free approach holds promise for improving early breast cancer diagnosis and patient outcomes.

Label-free detection of MiRNA biomarkers using broadband multi-resonant infrared metasurfaces for early breast cancer diagnosis.

Breast cancer is the most prevalent cancer globally. Early detection is crucial and can be achieved by detecting cancer biomarkers in blood, such as circulating miRNAs (microRNAs). In this study, we present a label-free detection method based on broadband multi-resonant infrared metasurface for surface-enhanced infrared absorption (SEIRA) spectroscopy to detect miRNAs. The SEIRA resonances were optimized to match the miRNA biomarker fingerprint regions in the range of 800 to 2000 cm-1 and 2800 to 3500 cm-1, resulting in a simulated resonance enhancement of up to 103 times. Nine patient samples (six cancerous and three non-cancerous) were measured using SEIRA multi-well sensor chips. A novel analysis method, SEIRA-AR, was also developed to benchmark the results against industry standards, such as quantitative reverse transcription polymerase chain reaction (RT-qPCR) and next-generation sequencing (NGS). Our results showed an excellent linear correlation with a Pearson's r value of up to 0.99 and an R Squared value of up to 0.98. This study represents the first use of a SEIRA sensor for biomarker detection on clinical breast cancer samples and introduces an analysis method that produces results comparable to industry standards. Our findings pave the way for routine cancer diagnosis in the future. Additionally, the method discussed can be generalized to other biosensing activities involving two-step binding processes with complementary molecule-capturing agents.

Circulating microRNA breast cancer biomarker detection in patient sera with surface plasmon resonance imaging biosensor.

In this article, we report for the first time, the detection of circulating miRNA as a breast cancer biomarker in patient sera using surface plasmon resonance imaging biosensor. The advantage of this approach lies in the rapid, label-free and sensitive detection. The sensor excites plasmonic resonance on the gold sensor surface and specific DNA-miRNA molecular bindings elucidate responses in the plasmonic resonance image. Experiments of detecting synthetic miRNA molecules (miR-1249) were performed and the sensor resolution was found to be 63.5 nM. The sensor was further applied to screen 17 patient serum samples from National Cancer Centre Singapore and Tan Tock Seng Hospital. Sensor intensity response was found to differ by 20% between malignant and benign cases and thus forms, a potential and an important metric in distinguishing benignity and malignancy.

Development of a microRNA Panel for Classification of Abnormal Mammograms for Breast Cancer.

Mammography is extensively used for breast cancer screening but has high false-positive rates. Here, prospectively collected blood samples were used to identify circulating microRNA (miRNA) biomarkers to discriminate between malignant and benign breast lesions among women with abnormal mammograms. The Discovery cohort comprised 72 patients with breast cancer and 197 patients with benign breast lesions, while the Validation cohort had 73 and 196 cancer and benign cases, respectively. Absolute expression levels of 324 miRNAs were determined using RT-qPCR. miRNA biomarker panels were identified by: (1) determining differential expression between malignant and benign breast lesions, (2) focusing on top differentially expressed miRNAs, and (3) building panels from an unbiased search among all expressed miRNAs. Two-fold cross-validation incorporating a feature selection algorithm and logistic regression was performed. A six-miRNA biomarker panel identified by the third strategy, had an area under the curve (AUC) of 0.785 and 0.774 in the Discovery and Validation cohorts, respectively, and an AUC of 0.881 when differentiating between cases versus those with benign lesions or healthy individuals with normal mammograms. Biomarker panel scores increased with tumor size, stage and number of lymph nodes involved. Our work demonstrates that circulating miRNA signatures can potentially be used with mammography to differentiate between patients with malignant and benign breast lesions.

Detection of genomic alterations in breast cancer with circulating tumour DNA sequencing.

Analysis of circulating cell-free DNA (cfDNA) has opened new opportunities for characterizing tumour mutational landscapes with many applications in genomic-driven oncology. We developed a customized targeted cfDNA sequencing approach for breast cancer (BC) using unique molecular identifiers (UMIs) for error correction. Our assay, spanning a 284.5 kb target region, is combined with a novel freely-licensed bioinformatics pipeline that provides detection of low-frequency variants, and reliable identification of copy number variations (CNVs) directly from plasma DNA. We first evaluated our pipeline on reference samples. Then in a cohort of 35 BC patients our approach detected actionable driver and clonal variants at low variant frequency levels in cfDNA that were concordant (77%) with sequencing of primary and/or metastatic solid tumour sites. We also detected ERRB2 gene CNVs used for HER2 subtype classification with 80% precision compared to immunohistochemistry. Further, we evaluated fragmentation profiles of cfDNA in BC and observed distinct differences compared to data from healthy individuals. Our results show that the developed assay addresses the majority of tumour associated aberrations directly from plasma DNA, and thus may be used to elucidate genomic alterations in liquid biopsy studies.

A Circulating miRNA Signature for Stratification of Breast Lesions among Women with Abnormal Screening Mammograms.

Although mammography is the gold standard for breast cancer screening, the high rates of false-positive mammograms remain a concern. Thus, there is an unmet clinical need for a non-invasive and reliable test to differentiate between malignant and benign breast lesions in order to avoid subjecting patients with abnormal mammograms to unnecessary follow-up diagnostic procedures. Serum samples from 116 malignant breast lesions and 64 benign breast lesions were comprehensively profiled for 2,083 microRNAs (miRNAs) using next-generation sequencing. Of the 180 samples profiled, three outliers were removed based on the principal component analysis (PCA), and the remaining samples were divided into training (n = 125) and test (n = 52) sets at a 70:30 ratio for further analysis. In the training set, significantly differentially expressed miRNAs (adjusted p < 0.01) were identified after correcting for multiple testing using a false discovery rate. Subsequently, a predictive classification model using an eight-miRNA signature and a Bayesian logistic regression algorithm was developed. Based on the receiver operating characteristic (ROC) curve analysis in the test set, the model could achieve an area under the curve (AUC) of 0.9542. Together, this study demonstrates the potential use of circulating miRNAs as an adjunct test to stratify breast lesions in patients with abnormal screening mammograms.

Assessment of PARP4 as a candidate breast cancer susceptibility gene.

PURPOSE: PARP4 has been proposed as a candidate breast cancer susceptibility gene. However, its function and involvement in breast carcinogenesis is unclear. We sought to determine the variant frequency of PARP4 in BRCA-negative women referred for genetic testing from Singapore and to perform functional analyses of PARP4. METHODS: Next-generation sequencing of PARP4 was conducted for 198 BRCA-negative cases from Singapore. Three independent case-control association analyses of PARP4 were performed for (1) our Singaporean cohort, (2) three dbGaP datasets, and (3) cases from TCGA, with controls from the Exome Aggregation Consortium (ExAC). PARP4 knockout cells were generated utilizing the CRISPR-Cas9 approach in MDA-MB-231 (breast cancer) and MCF10A (normal breast) cell lines, and colony formation, cell proliferation, and migration assays carried out. RESULTS: Candidate variants in PARP4 were identified in 5.5% (11/198) of our Singapore cohort. Case-control association studies for our cases and the dbGaP datasets showed no significant association. However, a significant association was observed for PARP4 variants when comparing 988 breast cancer cases from the TCGA provisional data and 53,105 controls from ExAC (ALL) (OR 0.249, 95% CI 0.139-0.414, P = 2.86 × 10-11). PARP4 knockout did not affect the clonogenicity, proliferation rate, and migration of normal breast cells, but appeared to decrease the proliferation rate and clonogenicity of breast cancer cells. CONCLUSIONS: Taken together, our results do not support that PARP4 functions as a cancer susceptibility gene. This study highlights the importance of performing functional analyses for candidate cancer predisposition genes.

Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese.

Genome-wide association studies (GWAS) have proven highly successful in identifying single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. The majority of these studies are on European populations, with limited SNP association data in other populations. We genotyped 51 GWAS-identified SNPs in two independent cohorts of Singaporean Chinese. Cohort 1 comprised 1294 BC cases and 885 controls and was used to determine odds ratios (ORs); Cohort 2 had 301 BC cases and 243 controls for deriving polygenic risk scores (PRS). After age-adjustment, 11 SNPs were found to be significantly associated with BC risk. Five SNPs were present in <1% of Cohort 1 and were excluded from further PRS analysis. To assess the cumulative effect of the remaining 46 SNPs on BC risk, we generated three PRS models: Model-1 included 46 SNPs; Model-2 included 11 statistically significant SNPs; and Model-3 included the SNPs in Model-2 but excluded SNPs that were in strong linkage disequilibrium with the others. Across Models-1, -2 and -3, women in the highest PRS quartile had the greatest ORs of 1.894 (95% CI = 1.157-3.100), 2.013 (95% CI = 1.227-3.302) and 1.751 (95% CI = 1.073-2.856) respectively, suggesting a direct correlation between PRS and BC risk. Given the potential of PRS in BC risk stratification, our findings suggest the need to tailor the selection of SNPs to be included in an ethnic-specific PRS model.

The future of blood-based biomarkers for the early detection of breast cancer.

Breast cancer (BC) is the most frequently diagnosed cancer and the most common cause of cancer-related mortality among women worldwide. Despite the extensive use of mammography as the gold standard for BC screening, the occurrences of false-positive and false-negative mammograms, as well as overdiagnosis, remain a concern in breast oncology. Thus, there is a need to identify reliable biomarkers from an easily accessible source that could generate cost-effective assays feasible for routine screening. Blood-based biomarkers may offer an alternative non-invasive strategy to improve cancer screening. Although none of the currently used blood-based biomarkers are sensitive enough for the early detection of BC, a plethora of significant findings pertaining to the development of screening tools using blood-based biomarkers have emerged in recent years. Promising candidate biomarkers such as proteins, autoantibodies, miRNAs, nucleic acid methylation, metabolites and lipids have shown great potential for detecting BC, including detection at the pre-invasive and early stages of the disease. Nevertheless, blood-based biomarkers for BC screening are still at the early phases of development, and various clinical and preclinical issues need to be addressed before these biomarkers can be used clinically. This review summarises the latest discoveries for harnessing blood-based biomarkers as novel BC screening tools, as well as discusses the limitations and challenges that need to be overcome before the translation of their use from the bench to the bedside.

Identification of Novel Breast Cancer Risk Loci.

It has been estimated that >1,000 genetic loci have yet to be identified for breast cancer risk. Here we report the first study utilizing targeted next-generation sequencing to identify single-nucleotide polymorphisms (SNP) associated with breast cancer risk. Targeted sequencing of 283 genes was performed in 240 women with early-onset breast cancer (≤40 years) or a family history of breast and/or ovarian cancer. Common coding variants with minor allele frequencies (MAF) >1% that were identified were presumed initially to be SNPs, but further database inspections revealed variants had MAF of ≤1% in the general population. Through prioritization and stringent selection criteria, we selected 24 SNPs for further genotyping in 1,516 breast cancer cases and 1,189 noncancer controls. Overall, we identified the JAK2 SNP rs56118985 to be significantly associated with overall breast cancer risk. Subtype analysis performed for patient subgroups defined by ER, PR, and HER2 status suggested additional associations of the NOTCH3 SNP rs200504060 and the HIF1A SNP rs142179458 with breast cancer risk. In silico analysis indicated that coding amino acids encoded at these three SNP sites were conserved evolutionarily and associated with decreased protein stability, suggesting a likely impact on protein function. Our results offer proof of concept for identifying novel cancer risk loci from next-generation sequencing data, with iterative data analysis from targeted, whole-exome, or whole-genome sequencing a wellspring to identify new SNPs associated with cancer risk. Cancer Res; 77(19); 5428-37. ©2017 AACR.

Whole-exome sequencing of breast cancer, malignant peripheral nerve sheath tumor and neurofibroma from a patient with neurofibromatosis type 1.

Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by the development of multiple neurofibromas, cafe-au-lait spots, and Lisch nodules. Individuals with NF1 are at increased risk of developing various tumors, such as malignant peripheral nerve sheath tumor (MPNST), pheochromocytoma, leukemia, glioma, rhabdomyosarcoma, and breast cancer. Here, we describe the exome sequencing of breast cancer, MPNST, and neurofibroma from a patient with NF1. We identified a germline mutation in the NF1 gene which resulted in conversion of leucine to proline at amino acid position 847. In addition, we showed independent somatic NF1 mutations in all the three tumors (frameshift insertion in breast cancer (p.A985fs), missense mutation in MPNST (p.G23R), and inframe deletion in dermal neurofibroma (p.L1876del-Inf)), indicating that a second hit in NF1 resulting in the loss of function could be important for tumor formation. Each tumor had a distinct genomic profile with mutually exclusive mutations in different genes. Copy number analysis revealed multiple copy number alterations in the breast cancer and the MPNST, but not the benign neurofibroma. Germline loss of chromosome 6q22.33, which harbors two potential tumor suppressor genes, PTPRK and LAMA2, was also identified; this may increase tumor predisposition further. In the background of NF1 syndrome, although second-hit NF1 mutation is critical in tumorigenesis, different additional mutations are required to drive the formation of different tumors.

Evaluation and optimisation of indel detection workflows for ion torrent sequencing of the BRCA1 and BRCA2 genes.

BACKGROUND: The Ion Torrent PGM is a popular benchtop sequencer that shows promise in replacing conventional Sanger sequencing as the gold standard for mutation detection. Despite the PGM's reported high accuracy in calling single nucleotide variations, it tends to generate many false positive calls in detecting insertions and deletions (indels), which may hinder its utility for clinical genetic testing. RESULTS: Recently, the proprietary analytical workflow for the Ion Torrent sequencer, Torrent Suite (TS), underwent a series of upgrades. We evaluated three major upgrades of TS by calling indels in the BRCA1 and BRCA2 genes. Our analysis revealed that false negative indels could be generated by TS under both default calling parameters and parameters adjusted for maximum sensitivity. However, indel calling with the same data using the open source variant callers, GATK and SAMtools showed that false negatives could be minimised with the use of appropriate bioinformatics analysis. Furthermore, we identified two variant calling measures, Quality-by-Depth (QD) and VARiation of the Width of gaps and inserts (VARW), which substantially reduced false positive indels, including non-homopolymer associated errors without compromising sensitivity. In our best case scenario that involved the TMAP aligner and SAMtools, we achieved 100% sensitivity, 99.99% specificity and 29% False Discovery Rate (FDR) in indel calling from all 23 samples, which is a good performance for mutation screening using PGM. CONCLUSIONS: New versions of TS, BWA and GATK have shown improvements in indel calling sensitivity and specificity over their older counterpart. However, the variant caller of TS exhibits a lower sensitivity than GATK and SAMtools. Our findings demonstrate that although indel calling from PGM sequences may appear to be noisy at first glance, proper computational indel calling analysis is able to maximize both the sensitivity and specificity at the single base level, paving the way for the usage of this technology for future clinical genetic testing.

Identification of circulating microRNA signatures for breast cancer detection.

PURPOSE: There is a quest for novel noninvasive diagnostic markers for the detection of breast cancer. The goal of this study is to identify circulating microRNA (miRNA) signatures using a cohort of Asian Chinese patients with breast cancer, and to compare miRNA profiles between tumor and serum samples. EXPERIMENTAL DESIGN: miRNA from paired breast cancer tumors, normal tissue, and serum samples derived from 32 patients were comprehensively profiled using microarrays or locked nucleic acid real-time PCR panels. Serum samples from healthy individuals (n = 22) were also used as normal controls. Significant serum miRNAs, identified by logistic regression, were validated in an independent set of serum samples from patients (n = 132) and healthy controls (n = 101). RESULTS: The 20 most significant miRNAs differentially expressed in breast cancer tumors included miRNA (miR)-21, miR-10b, and miR-145, previously shown to be dysregulated in breast cancer. Only 7 miRNAs were overexpressed in both tumors and serum, suggesting that miRNAs may be released into the serum selectively. Interestingly, 16 of the 20 most significant miRNAs differentially expressed in serum samples were novel. MiR-1, miR-92a, miR-133a, and miR-133b were identified as the most important diagnostic markers, and were successfully validated; receiver operating characteristic curves derived from combinations of these miRNAs exhibited areas under the curves of 0.90 to 0.91. CONCLUSION: The clinical use of miRNA signatures as a noninvasive diagnostic strategy is promising, but should be further validated for different subtypes of breast cancers.

Improving indel detection specificity of the Ion Torrent PGM benchtop sequencer.

The emergence of benchtop sequencers has made clinical genetic testing using next-generation sequencing more feasible. Ion Torrent's PGM™ is one such benchtop sequencer that shows clinical promise in detecting single nucleotide variations (SNVs) and microindel variations (indels). However, the large number of false positive indels caused by the high frequency of homopolymer sequencing errors has impeded PGM™'s usage for clinical genetic testing. An extensive analysis of PGM™ data from the sequencing reads of the well-characterized genome of the Escherichia coli DH10B strain and sequences of the BRCA1 and BRCA2 genes from six germline samples was done. Three commonly used variant detection tools, SAMtools, Dindel, and GATK's Unified Genotyper, all had substantial false positive rates for indels. By incorporating filters on two major measures we could dramatically improve false positive rates without sacrificing sensitivity. The two measures were: B-Allele Frequency (BAF) and VARiation of the Width of gaps and inserts (VARW) per indel position. A BAF threshold applied to indels detected by UnifiedGenotyper removed ~99% of the indel errors detected in both the DH10B and BRCA sequences. The optimum BAF threshold for BRCA sequences was determined by requiring 100% detection sensitivity and minimum false discovery rate, using variants detected from Sanger sequencing as reference. This resulted in 15 indel errors remaining, of which 7 indel errors were removed by selecting a VARW threshold of zero. VARW specific errors increased in frequency with higher read depth in the BRCA datasets, suggesting that homopolymer-associated indel errors cannot be reduced by increasing the depth of coverage. Thus, using a VARW threshold is likely to be important in reducing indel errors from data with higher coverage. In conclusion, BAF and VARW thresholds provide simple and effective filtering criteria that can improve the specificity of indel detection in PGM™ data without compromising sensitivity.

Development of a next-generation sequencing method for BRCA mutation screening: a comparison between a high-throughput and a benchtop platform.

In a clinical setting, next-generation sequencing (NGS) approaches for the enrichment and resequencing of DNA targets may have limitations in throughput, cost, or accuracy. We evaluated an NGS workflow for targeted DNA sequencing for mutation detection. Targeted sequence data of the BRCA1 and BRCA2 genes, generated using a PCR-based, multiplexed NGS approach using the SOLiD 4 (n = 24) and Ion Torrent PGM (n = 20) next-generation sequencers, were evaluated against sequence data obtained by Sanger sequencing. The overall sensitivity for SOLiD and PGM were 97.8% (95% CI = 94.7 to 100.0) and 98.9% (95% CI = 96.8 to 100.0) respectively. The specificity for the SOLiD platform was high, at 100.0% (95% CI = 99.3 to 100.0). PGM correctly identified all 3 indels, but 68 false-positive indels were also called. Equimolar normalization of amplicons was not necessary for successful NGS. Both platforms are highly amenable to scale-up, potentially reducing the reagent cost for BRCA testing to

Evaluation of nanofluidics technology for high-throughput SNP genotyping in a clinical setting.

The current need for high-throughput genotyping platforms for targeted validation of disease-associated single nucleotide polymorphisms (SNPs) motivated us to evaluate a novel nanofluidics platform for genotyping DNA extracted from peripheral blood and buccal wash samples. SNP genotyping was performed using a Fluidigm 48.48 Dynamic Array biochip on the BioMark polymerase chain reaction platform and results were compared against standard TaqMan assays and DNA sequencing. Pilot runs using these dynamic arrays on 90 samples against 20 SNP assays had an average call rate of 99.7%, with 100% call rates for 16 of the assays. Manual TaqMan genotyping of these samples against three SNPs demonstrated 100% correlation between the two platforms. To understand the influence of DNA template variability, three sources of blood samples (CH-1, n = 20; CH-2, n = 47; KK, n = 47) and buccal washes (n = 37) were genotyped for 24 SNPs. Although both CH-1 and CH-2 batches showed good base calling (≥98.8%), the KK batch and buccal wash samples exhibited lower call rates (82.1% and 94.0%). Importantly, repurification of the KK and buccal wash samples resulted in significant improvements in their call rates (to ≥97.9%). Scale-up for genotyping 1698 cases and controls for 24 SNPs had overall call rates of 97.6% for KK and 99.2% for CH samples. The Dynamic Array approach demonstrated accuracy similar to that of TaqMan genotyping, while offering significant savings in DNA, effort, time, and costs.

Direct detection of isoniazid-resistant Mycobacterium tuberculosis in respiratory specimens by multiplex allele-specific polymerase chain reaction.

This study evaluated the feasibility of using 2 multiplex allele-specific polymerase chain reaction (MAS-PCR) assays targeting 2 mutations (codon 315 of the katG gene and the 15th nucleotide preceding the mabA-inhA operon) to directly detect isoniazid (INH)-resistant Mycobacterium tuberculosis in cultured isolates and respiratory specimens. A total of 203 M. tuberculosis isolates and 487 respiratory specimens were investigated. The MAS-PCR assays successfully amplified all M. tuberculosis isolates and acid-fast bacilli smear-positive specimens while only 49.2% of the smear-negative specimens exhibited positive MAS-PCR results. The MAS-PCR assays identified 83.4% and 79.2% of the resistant strains in the culture isolates and respiratory specimens, respectively. All the inferred genotypes were in complete accordance with subsequent DNA sequence analyses. This study suggested the application of our improved MAS-PCR protocols to provide the rapid identification of INH-resistant M. tuberculosis directly in respiratory specimens. The technical simplicity, short turnaround time, and low cost of this molecular strategy should facilitate routine diagnostic services in developing areas with a high prevalence of drug-resistant tuberculosis.

Overexpression of RB1 transcript is significantly correlated with 13q14 allelic imbalance in colorectal carcinomas.

RB1 gene expression has been reported to be upregulated in colorectal carcinomas (CRC) at both the mRNA and protein levels when compared to normal colonic mucosa. However, allelic loss at the genomic level has been detected in CRC with widely differing frequencies ranging from 11.5% to 50%. To determine whether there is indeed a correlation between RB1 allelic imbalance (AI) and expression, a consecutive series of 55 CRC from Singapore patients were analysed by microsatellite analysis, real-time RT-PCR and immunohistochemistry. Microsatellite analysis using 3 RB1 intragenic microsatellite markers and 2 markers flanking RB1 detected AI in 32.7% (18/55) of the cases, in at least 1 locus. The highest AI frequency (22.9%) was observed at the microsatellite marker D13S137 (Cu13), which maps 5 cM distal to RB1. AI was present in both early and late Dukes stages. Real-time RT-PCR revealed that all 40 cases analysed expressed RB1 mRNA, with mRNA overexpression in 37.5% (15/40) and pRB protein expression in 88.2% (30/34) of cases. Notably, a statistically significant correlation was found between AI of RB1 and mRNA overexpression of RB1 (p < 0.001, Fishers exact test). These findings provide evidence that despite AI, RB1 expression is not abrogated. Thus, our data suggests that RB1 may play a role in colorectal tumorigenesis through functional regulation of the transcript and protein rather than through its tumour suppressor role by gene inactivation.