Minimally invasive biopsy-based diagnostics in support of precision cancer medicine.

Precision cancer medicine (PCM) to support the treatment of solid tumors requires minimally invasive diagnostics. Here, we describe the development of fine-needle aspiration biopsy-based (FNA) molecular cytology which will be increasingly important in diagnostics and adaptive treatment. We provide support for FNA-based molecular cytology having a significant potential to replace core needle biopsy (CNB) as a patient-friendly potent technique for tumor sampling for various tumor types. This is not only because CNB is a more traumatic procedure and may be associated with more complications compared to FNA-based sampling, but also due to the recently developed molecular methods used with FNA. Recent studies show that image-guided FNA in combination with ultrasensitive molecular methods also offers opportunities for characterization of the tumor microenvironment which can aid therapeutic decisions. Here we provide arguments for an increased implementation of molecular FNA-based sampling as a patient-friendly diagnostic method, which may, due to its repeatability, facilitate regular sampling that is needed during different treatment lines, to provide tumor information, supporting treatment decisions, shortening lead times in healthcare, and benefit healthcare economics.

Multiplex protein analysis and ensemble machine learning methods of fine needle aspirates from prostate cancer patients reveal potential diagnostic signatures associated with tumour grade.

BACKGROUND: Improved molecular diagnosis is needed in prostate cancer (PC). Fine needle aspiration (FNA) is a minimally invasive biopsy technique, less traumatic compared to core needle biopsy, and could be useful for diagnosis of PC. Molecular biomarkers (BMs) in FNA-samples can be assessed for prediction, eg of immunotherapy efficacy before treatment as well as at treatment decision time points during disease progression. METHODS: In the present pilot study, the expression levels of 151 BM proteins were analysed by proximity extension assay in FNA-samples from 16 patients, including benign prostate lesions (n = 3) and cancers (n = 13). An ensemble data analysis strategy was applied using several machine learning models. RESULTS: Twelve potentially predictive BM proteins correlating with International Society of Urological Pathology grade groups were identified, among them vimentin, tissue factor pathway inhibitor 2, and integrin beta-5. The validity of the results was supported by network analysis that showed functional associations between most of the identified putative BMs. We also showed that multiple immune checkpoint targets can be assessed (eg PD-L1, CD137, and Galectin-9), which may support the selection of immunotherapy in advanced PC. Results are promising but need further validation in a larger cohort. CONCLUSIONS: Our pilot study represents a "proof of concept" and shows that multiplex profiling of potential diagnostic and predictive BM proteins is feasible on tumour material obtained by FNA sampling of prostate cancer. Moreover, our results demonstrate that an ensemble data analysis strategy may facilitate the identification of BM signatures in pilot studies when the patient cohort is limited.

Fast, streamlined fluorescence nanoscopy resolves rearrangements of SNARE and cargo proteins in platelets co-incubated with cancer cells.

BACKGROUND: Increasing evidence suggests that platelets play a central role in cancer progression, with altered storage and selective release from platelets of specific tumor-promoting proteins as a major mechanism. Fluorescence-based super-resolution microscopy (SRM) can resolve nanoscale spatial distribution patterns of such proteins, and how they are altered in platelets upon different activations. Analysing such alterations by SRM thus represents a promising, minimally invasive strategy for platelet-based diagnosis and monitoring of cancer progression. However, broader applicability beyond specialized research labs will require objective, more automated imaging procedures. Moreover, for statistically significant analyses many SRM platelet images are needed, of several different platelet proteins. Such proteins, showing alterations in their distributions upon cancer progression additionally need to be identified. RESULTS: A fast, streamlined and objective procedure for SRM platelet image acquisition, analysis and classification was developed to overcome these limitations. By stimulated emission depletion SRM we imaged nanoscale patterns of six different platelet proteins; four different SNAREs (soluble N-ethylmaleimide factor attachment protein receptors) mediating protein secretion by membrane fusion of storage granules, and two angiogenesis regulating proteins, representing cargo proteins within these granules coupled to tumor progression. By a streamlined procedure, we recorded about 100 SRM images of platelets, for each of these six proteins, and for five different categories of platelets; incubated with cancer cells (MCF-7, MDA-MB-231, EFO-21), non-cancer cells (MCF-10A), or no cells at all. From these images, structural similarity and protein cluster parameters were determined, and probability functions of these parameters were generated for the different platelet categories. By comparing these probability functions between the categories, we could identify nanoscale alterations in the protein distributions, allowing us to classify the platelets into their correct categories, if they were co-incubated with cancer cells, non-cancer cells, or no cells at all. CONCLUSIONS: The fast, streamlined and objective acquisition and analysis procedure established in this work confirms the role of SNAREs and angiogenesis-regulating proteins in platelet-mediated cancer progression, provides additional fundamental knowledge on the interplay between tumor cells and platelets, and represent an important step towards using tumor-platelet interactions and redistribution of nanoscale protein patterns in platelets as a basis for cancer diagnostics.

SATB1, genomic instability and Gleason grading constitute a novel risk score for prostate cancer.

Current prostate cancer risk classifications rely on clinicopathological parameters resulting in uncertainties for prognostication. To improve individual risk stratification, we examined the predictive value of selected proteins with respect to tumor heterogeneity and genomic instability. We assessed the degree of genomic instability in 50 radical prostatectomy specimens by DNA-Image-Cytometry and evaluated protein expression in related 199 tissue-microarray (TMA) cores. Immunohistochemical data of SATB1, SPIN1, TPM4, VIME and TBB5 were correlated with the degree of genomic instability, established clinical risk factors and overall survival. Genomic instability was associated with a GS ≥ 7 (p = 0.001) and worse overall survival (p = 0.008). A positive SATB1 expression was associated with a GS ≤ 6 (p = 0.040), genomic stability (p = 0.027), and was a predictor for increased overall survival (p = 0.023). High expression of SPIN1 was also associated with longer overall survival (p = 0.048) and lower preoperative PSA-values (p = 0.047). The combination of SATB1 expression, genomic instability, and GS lead to a novel Prostate Cancer Prediction Score (PCP-Score) which outperforms the current D'Amico et al. stratification for predicting overall survival. Low SATB1 expression, genomic instability and GS ≥ 7 were identified as markers for poor prognosis. Their combination overcomes current clinical risk stratification regimes.

PITX2 DNA-Methylation: Predictive versus Prognostic Value for Anthracycline-Based Chemotherapy in Triple-Negative Breast Cancer Patients.

BACKGROUND: PITX2 DNA methylation has been shown to predict outcomes in high-risk breast cancer patients after anthracycline-based chemotherapy. To determine its prognostic versus predictive value, the impact of PITX2 DNA methylation on outcomes was studied in an untreated cohort vs. an anthracycline-treated triple-negative breast cancer (TNBC) cohort. MATERIAL AND METHODS: The percent DNA methylation ratio (PMR) of paired-like homeodomain transcription factor 2 (PITX2) was determined by a validated methylation-specific real-time PCR test. Patient samples of routinely collected archived formalin-fixed paraffin-embedded (FFPE) tissue and clinical data from 144 TNBC patients of 2 independent cohorts (i.e., 66 untreated patients and 78 patients treated with anthracycline-based chemotherapy) were analyzed. RESULTS: The risk of 5- and 10-year overall survival (OS) increased continuously with rising PITX2 DNA methylation in the anthracycline-treated population, but it increased only slightly during 10-year follow-up time in the untreated patient population. PITX2 DNA methylation with a PMR cutoff of 2 did not show significance for poor vs. good outcomes (OS) in the untreated patient cohort (HR = 1.55; p = 0.259). In contrast, the PITX2 PMR cutoff of 2 identified patients with poor (PMR >2) vs. good (PMR ≤2) outcomes (OS) with statistical significance in the anthracycline-treated cohort (HR = 3.96; p = 0.011). The results in the subgroup of patients who did receive anthracyclines only (no taxanes) confirmed this finding (HR = 5.71; p = 0.014). CONCLUSION: In this hypothesis-generating study PITX2 DNA methylation demonstrated predominantly predictive value in anthracycline treatment in TNBC patients. The risk of poor outcome (OS) correlates with increasing PITX2 DNA methylation.

Hard wiring of normal tissue-specific chromosome-wide gene expression levels is an additional factor driving cancer type-specific aneuploidies.

BACKGROUND: Many carcinomas have recurrent chromosomal aneuploidies specific to the tissue of tumor origin. The reason for this specificity is not completely understood. METHODS: In this study, we looked at the frequency of chromosomal arm gains and losses in different cancer types from the The Cancer Genome Atlas (TCGA) and compared them to the mean gene expression of each chromosome arm in corresponding normal tissues of origin from the Genotype-Tissue Expression (GTEx) database, in addition to the distribution of tissue-specific oncogenes and tumor suppressors on different chromosome arms. RESULTS: This analysis revealed a complex picture of factors driving tumor karyotype evolution in which some recurrent chromosomal copy number reflect the chromosome arm-wide gene expression levels of the their normal tissue of tumor origin. CONCLUSIONS: We conclude that the cancer type-specific distribution of chromosomal arm gains and losses is potentially "hardwiring" gene expression levels characteristic of the normal tissue of tumor origin, in addition to broadly modulating the expression of tissue-specific tumor driver genes.

Genome Instability Profiles Predict Disease Outcome in a Cohort of 4,003 Patients with Breast Cancer.

PURPOSE: The choice of therapy for patients with breast cancer is often based on clinicopathologic parameters, hormone receptor status, and HER2 amplification. To improve individual prognostication and tailored treatment decisions, we combined clinicopathologic prognostic data with genome instabilty profiles established by quantitative measurements of the DNA content. EXPERIMENTAL DESIGN: We retrospectively assessed clinical data of 4,003 patients with breast cancer with a minimum postoperative follow-up period of 10 years. For the entire cohort, we established genome instability profiles. We applied statistical methods, including correlation matrices, Kaplan-Meier curves, and multivariable Cox proportional hazard models, to ascertain the potential of standard clinicopathologic data and genome instability profiles as independent predictors of disease-specific survival in distinct subgroups, defined clinically or with respect to treatment. RESULTS: In Cox regression analyses, two parameters of the genome instability profiles, the S-phase fraction and the stemline scatter index, emerged as independent predictors in premenopausal women, outperforming all clinicopathologic parameters. In postmenopausal women, age and hormone receptor status were the predominant prognostic factors. However, by including S-phase fraction and 2.5c exceeding rate, we could improve disease outcome prediction in pT1 tumors irrespective of the lymph node status. In pT3-pT4 tumors, a higher S-phase fraction led to poorer prognosis. In patients who received adjuvant endocrine therapy, chemotherapy or radiotherapy, or a combination, the ploidy profiles improved prognostication. CONCLUSIONS: Genome instability profiles predict disease outcome in patients with breast cancer independent of clinicopathologic parameters. This applies especially to premenopausal patients. In patients receiving adjuvant therapy, the profiles improve identification of high-risk patients.

High Levels of Chromosomal Copy Number Alterations and TP53 Mutations Correlate with Poor Outcome in Younger Breast Cancer Patients.

Prognosis in young patients with breast cancer is generally poor, yet considerable differences in clinical outcomes between individual patients exist. To understand the genetic basis of the disparate clinical courses, tumors were collected from 34 younger women, 17 with good and 17 with poor outcomes, as determined by disease-specific survival during a follow-up period of 17 years. The clinicopathologic parameters of the tumors were complemented with DNA image cytometry profiles, enumeration of copy numbers of eight breast cancer genes by multicolor fluorescence in situ hybridization, and targeted sequence analysis of 563 cancer genes. Both groups included diploid and aneuploid tumors. The degree of intratumor heterogeneity was significantly higher in aneuploid versus diploid cases, and so were gains of the oncogenes MYC and ZNF217. Significantly more copy number alterations were observed in the group with poor outcome. Almost all tumors in the group with long survival were classified as luminal A, whereas triple-negative tumors predominantly occurred in the short survival group. Mutations in PIK3CA were more common in the group with good outcome, whereas TP53 mutations were more frequent in patients with poor outcomes. This study shows that TP53 mutations and the extent of genomic imbalances are associated with poor outcome in younger breast cancer patients and thus emphasize the central role of genomic instability vis-a-vis tumor aggressiveness.

Super-resolution microscopy can identify specific protein distribution patterns in platelets incubated with cancer cells.

Protein contents in platelets are frequently changed upon tumor development and metastasis. However, how cancer cells can influence protein-selective redistribution and release within platelets, thereby promoting tumor development, remains largely elusive. With fluorescence-based super-resolution stimulated emission depletion (STED) imaging we reveal how specific proteins, implicated in tumor progression and metastasis, re-distribute within platelets, when subject to soluble activators (thrombin, adenosine diphosphate and thromboxane A2), and when incubated with cancer (MCF-7, MDA-MB-231, EFO21) or non-cancer cells (184A1, MCF10A). Upon cancer cell incubation, the cell-adhesion protein P-selectin was found to re-distribute into circular nano-structures, consistent with accumulation into the membrane of protein-storing alpha-granules within the platelets. These changes were to a significantly lesser extent, if at all, found in platelets incubated with normal cells, or in platelets subject to soluble platelet activators. From these patterns, we developed a classification procedure, whereby platelets exposed to cancer cells, to non-cancer cells, soluble activators, as well as non-activated platelets all could be identified in an automatic, objective manner. We demonstrate that STED imaging, in contrast to electron and confocal microscopy, has the necessary spatial resolution and labelling efficiency to identify protein distribution patterns in platelets and can resolve how they specifically change upon different activations. Combined with image analyses of specific protein distribution patterns within the platelets, STED imaging can thus have a role in future platelet-based cancer diagnostics and therapeutic monitoring. The presented approach can also bring further clarity into fundamental mechanisms for cancer cell-platelet interactions, and into non-contact cell-to-cell interactions in general.

Protein profiling of fine-needle aspirates reveals subtype-associated immune signatures and involvement of chemokines in breast cancer.

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and for follow-up of personalized cancer therapy, including immunotherapy. Fine-needle aspiration (FNA) biopsy provides ready access to relevant tissue samples; however, the minute amounts of sample require sensitive multiplex molecular analysis to be of clinical biomarker utility. We have applied proximity extension assays (PEA) to analyze 167 proteins in FNA samples from patients with breast cancer (BC; n = 25) and benign lesions (n = 32). We demonstrate that the FNA BC samples could be divided into two main clusters, characterized by differences in expression levels of the estrogen receptor (ER) and the proliferation marker Ki67. This clustering corresponded to some extent to established BC subtypes. Our analysis also revealed several proteins whose expression levels differed between BC and benign lesions (e.g., CA9, GZMB, IL-6, VEGFA, CXCL11, PDL1, and PCD1), as well as several chemokines correlating with ER and Ki67 status (e.g., CCL4, CCL8, CCL20, CXCL8, CXCL9, and CXCL17). Finally, we also identified three signatures that could predict Ki67 status, ER status, and tumor grade, respectively, based on a small subset of proteins, which was dominated by chemokines. To our knowledge, expression profiles of CCL13 in benign lesions and BC have not previously been described but were shown herein to correlate with proliferation (P = 0.00095), suggesting a role in advanced BC. Given the broad functional range of the proteins analyzed, immune-related proteins were overrepresented among the observed alterations. Our pilot study supports the emerging role of chemokines in BC progression. Due to the minimally traumatic sampling and clinically important molecular information for therapeutic decisions, this methodology is promising for future immunoscoring and monitoring of treatment efficacy in BC.

A fine-needle aspiration-based protein signature discriminates benign from malignant breast lesions.

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and to follow-up personalized cancer therapy. Fine-needle aspiration (FNA) biopsy provides ready access to relevant tissues; however, the minute sample amounts require sensitive multiplex molecular analysis to achieve clinical utility. We have applied proximity extension assays (PEA) and NanoString (NS) technology for analyses of proteins and of RNA, respectively, in FNA samples. Using samples from patients with breast cancer (BC, n = 25) or benign lesions (n = 33), we demonstrate that these FNA-based molecular analyses (a) can offer high sensitivity and reproducibility, (b) may provide correct diagnosis in shorter time and at a lower cost than current practice, (c) correlate with results from routine analysis (i.e., benchmarking against immunohistochemistry tests for ER, PR, HER2, and Ki67), and (d) may also help identify new markers related to immunotherapy. A specific 11-protein signature, including FGF binding protein 1, decorin, and furin, distinguished all cancer patient samples from all benign lesions in our main cohort and in smaller replication cohort. Due to the minimally traumatic sampling and rich molecular information, this combined proteomics and transcriptomic methodology is promising for diagnostics and evaluation of treatment efficacy in BC.

Platelet protein biomarker panel for ovarian cancer diagnosis.

BACKGROUND: Platelets support cancer growth and spread making platelet proteins candidates in the search for biomarkers. METHODS: Two-dimensional (2D) gel electrophoresis, Partial Least Squares Discriminant Analysis (PLS-DA), Western blot, DigiWest. RESULTS: PLS-DA of platelet protein expression in 2D gels suggested differences between the International Federation of Gynaecology and Obstetrics (FIGO) stages III-IV of ovarian cancer, compared to benign adnexal lesions with a sensitivity of 96% and a specificity of 88%. A PLS-DA-based model correctly predicted 7 out of 8 cases of FIGO stages I-II of ovarian cancer after verification by western blot. Receiver-operator curve (ROC) analysis indicated a sensitivity of 83% and specificity of 76% at cut-off >0.5 (area under the curve (AUC) = 0.831, p < 0.0001) for detecting these cases. Validation on an independent set of samples by DigiWest with PLS-DA differentiated benign adnexal lesions and ovarian cancer, FIGO stages III-IV, with a sensitivity of 70% and a specificity of 83%. CONCLUSION: We identified a group of platelet protein biomarker candidates that can quantify the differential expression between ovarian cancer cases as compared to benign adnexal lesions.

Protein levels of clusterin and glutathione synthetase in platelets allow for early detection of colorectal cancer.

Colorectal cancer (CRC) is one of the most frequent malignancies in the Western world. Early tumor detection and intervention are important determinants on CRC patient survival. During early tumor proliferation, dissemination and angiogenesis, platelets store and segregate proteins actively and selectively. Hence, the platelet proteome is a potential source of biomarkers denoting early malignancy. By comparing protein profiles of platelets between healthy volunteers (n = 12) and patients with early- (n = 7) and late-stage (n = 5) CRCs using multiplex fluorescence two-dimensional gel electrophoresis (2D-DIGE), we aimed at identifying differentially regulated proteins within platelets. By inter-group comparisons, 94 differentially expressed protein spots were detected (p < 0.05) between healthy controls and patients with early- and late-stage CRCs and revealed distinct separations between all three groups in principal component analyses. 54 proteins of interest were identified by mass spectrometry and resulted in high-ranked Ingenuity Pathway Analysis networks associated with Cellular function and maintenance, Cellular assembly and organization, Developmental disorder and Organismal injury and abnormalities (p < 0.0001 to p = 0.0495). Target proteins were validated by multiplex fluorescence-based Western blot analyses using an additional, independent cohort of platelet protein samples [healthy controls (n = 15), early-stage CRCs (n = 15), late-stage CRCs (n = 15)]. Two proteins-clusterin and glutathione synthetase (GSH-S)-featured high impact and were subsequently validated in this independent clinical cohort distinguishing healthy controls from patients with early- and late-stage CRCs. Thus, the potential of clusterin and GSH-S as platelet biomarkers for early detection of CRC could improve existing screening modalities in clinical application and should be confirmed in a prospective multicenter trial.

Aneuploidy, TP53 mutation, and amplification of MYC correlate with increased intratumor heterogeneity and poor prognosis of breast cancer patients.

The clinical course of breast cancer varies from one patient to another. Currently, the choice of therapy relies on clinical parameters and histological and molecular tumor features. Alas, these markers are informative in only a subset of patients. Therefore, additional predictors of disease outcome would be valuable for treatment stratification. Extensive studies showed that the degree of variation of the nuclear DNA content, i.e., aneuploidy, determines prognosis. Our aim was to further elucidate the molecular basis of aneuploidy. We analyzed five diploid and six aneuploid tumors with more than 20 years of follow-up. By performing FISH with a multiplexed panel of 10 probes to enumerate copy numbers in individual cells, and by sequencing 563 cancer-related genes, we analyzed how aneuploidy is linked to intratumor heterogeneity. In our cohort, none of the patients with diploid tumors died of breast cancer during follow-up in contrast to four of six patients with aneuploid tumors (mean survival 86.4 months). The FISH analysis showed markedly increased genomic instability and intratumor heterogeneity in aneuploid tumors. MYC gain was observed in only 20% of the diploid cancers, while all aneuploid cases showed a gain. The mutation burden was similar in diploid and aneuploid tumors, however, TP53 mutations were not observed in diploid tumors, but in all aneuploid tumors in our collective. We conclude that quantitative measurements of intratumor heterogeneity by multiplex FISH, detection of MYC amplification and TP53 mutation could augment prognostication in breast cancer patients.

Core-needle biopsy of breast cancer is associated with a higher rate of distant metastases 5 to 15 years after diagnosis than FNA biopsy.

BACKGROUND: The literature offers discordant results regarding whether diagnostic biopsy is associated with the dissemination of cancer cells, resulting in local and/or distant metastasis. The long-term outcomes of patients with breast cancer were compared between those who were diagnosed using either fine-needle aspiration biopsy (FNAB) or core-needle biopsy (CNB) during 2 decades: the 1970s and 1990s. METHODS: In the 1970s, the only diagnostic needle biopsy method used for breast cancer in Sweden was FNAB. CNB was introduced 1989 and became established in Stockholm Gotland County in the early 1990s. The authors compared the clinical outcomes of patients diagnosed using FNAB from 1971 to 1976 (n = 354) versus those of patients diagnosed using CNB from 1991 to 1995 (n = 1729). Adjusting for differences in various treatment modalities, mammography screening, tumor size, DNA ploidy, and patient age between the 2 decades, 2 strictly matched samples representing FNAB (n = 181) and CNB (n = 203) were selected for a 15-year follow-up study. RESULTS: In a comparison of the rates of distant metastasis in the strictly matched patient groups from the FNAB and CNB cohorts, significantly higher rates of late-appearing (5-15 years after diagnosis) distant metastasis were observed among the patients who were diagnosed on CNB compared with those who were diagnosed on FNAB. No significant difference in local metastasis was observed between the 2 groups. CONCLUSIONS: At 5 to 15 years after diagnosis of the primary tumor, CNB-diagnosed patients had significantly higher rates of distant metastases than FNAB-diagnosed patients. Cancer Cytopathol 2017;125:748-56. © 2017 American Cancer Society.

Patterns of acute inflammatory symptoms prior to cancer diagnosis.

Although many studies have examined the role of chronic inflammation in cancer development, few studies discuss the patterns of acute inflammation prior to cancer diagnosis. Patients with lung, colorectal, prostate, or breast cancer between 1 July 2006 and 31 December 2009 and their metastatic status at diagnosis were determined through the Swedish Cancer Register. Non-steroidal anti-inflammatory drugs (NSAIDs) use in the year prior to cancer diagnosis was assessed through the Swedish Prescribed Drug Register. There were 13,945 patients identified with breast cancer, 6501 with prostate cancer, 5508 with lung cancer, and 12,723 with colon cancer. For metastatic patients, there is strong evidence of higher NSAIDs use 1-3 months compared to 10-12 months prior to diagnosis (breast odds ratio (OR) = 3.54, 95% CI 2.26-5.54; prostate OR = 3.90, 95% CI 3.10-4.90; lung OR = 2.90 95% CI 2.44-3.44; colorectal OR = 1.67, 95% CI 1.36-2.05). For non-metastatic patients, increased NSAIDs use 1-3 months prior to diagnosis was also observed, but only to a smaller extent for lung and prostate cancer (prostate OR = 1.48, 95% CI 1.27-1.72; lung 1.41, 95% CI 1.19-1.67). In conclusion, if NSAIDs use reflects underlying inflammatory symptoms, there is support for the hypothesis that advanced cancer was associated with an acute inflammatory process.

A new method to gently place biopsy needles or treatment electrodes into tissues with high target precision.

We present a new core needle biopsy and treatment electrode precision placement technique which, regardless of needle size, target lesion hardness and elasticity, makes it possible to precisely place an image guided device inside the abnormal tissue. Once inside the abnormal lesion, multiple tissue samples can be collected using a dedicated trocar and collecting system. Our unique "Fourier" driver substitutes the commonly used spring-loaded device or complements the jerky insertion technique used by experienced interventional physicians. It enables the physician to precisely and with extreme tactility maneuver even large diameter core needles or treatment-electrodes into the lesion using only a diminutive external force. This is achieved by applying supporting servo-controlled mechanical high-acceleration micro-pulses, proportional to the average vector directed by the physician. The Fourier-needle or Fourier-electrode stands completely non-moving when the system automatically goes into full idling. This means that the angle of attack successively and arbitrary can be aligned to hit the target, becoming successively symmetrically inserted into even small tumors to be treated as well as exactly hit any point outlined by real time ultrasound guiding. This kind of biopsy needle or treatment electrode placement results in a uniquely accurate and less traumatic procedure. Due to the risk of disseminating viable tumor cells the precision placement device can be combined with a computer controlled anti-seeding system, denaturizing tumor cells detached during penetration of the biopsy needle or treatment electrode.

Phylogenetic analysis of multiple FISH markers in oral tongue squamous cell carcinoma suggests that a diverse distribution of copy number changes is associated with poor prognosis.

Oral tongue squamous cell carcinoma (OTSCC) is associated with poor prognosis. To improve prognostication, we analyzed four gene probes (TERC, CCND1, EGFR and TP53) and the centromere probe CEP4 as a marker of chromosomal instability, using fluorescence in situ hybridization (FISH) in single cells from the tumors of sixty-five OTSCC patients (Stage I, n = 15; Stage II, n = 30; Stage III, n = 7; Stage IV, n = 13). Unsupervised hierarchical clustering of the FISH data distinguished three clusters related to smoking status. Copy number increases of all five markers were found to be correlated to non-smoking habits, while smokers in this cohort had low-level copy number gains. Using the phylogenetic modeling software FISHtrees, we constructed models of tumor progression for each patient based on the four gene probes. Then, we derived test statistics on the models that are significant predictors of disease-free and overall survival, independent of tumor stage and smoking status in multivariate analysis. The patients whose tumors were modeled as progressing by a more diverse distribution of copy number changes across the four genes have poorer prognosis. This is consistent with the view that multiple genetic pathways need to become deregulated in order for cancer to progress.

Genetic Instability and Disease Prognostication.

Genetic instability is a striking feature of human cancers, with an impact on the genesis, progression and prognosis. The clinical importance of genomic instability and aneuploidy is underscored by its association with poor patient outcome in multiple cancer types, including breast and colon cancer. Interestingly, there is growing evidence that prognostic gene expression signatures simply reflect the degree of genomic instability. Additionally, also the proteome is affected by aneuploidy and has therefore become a powerful tool to screen for new targets for therapy, diagnosis and prognostication. In this context, the chapter presents the impact of genomic instability on disease prognostication occurring in human cancers.

A standardized method for quantifying proliferation by Ki-67 and cyclin A immunohistochemistry in breast cancer.

Immunohistochemical analysis of proliferation markers such as Ki-67 and cyclin A is widely used in clinical evaluation as a prognostic factor in breast cancer. The proliferation status of tumors is guiding the decision of whether or not a patient should be treated with chemotherapy because low-proliferative tumors are less sensitive by such treatment. However, the lack of optimal cutoff points and selection of tumor areas hamper its use in clinical practice. This study was performed to compare the Ki-67 and cyclin A expression counted in hot-spot vs average counting based on 5 to 14 random tumor areas in 613 breast carcinomas. We correlated the findings with 10-year follow-up in order to standardize the evaluation of proliferation markers in clinical practice. A significant correlation was found between the percentage of positive cells estimated by Ki-67 and cyclin A both by hot-spot and by average counting. Both methods showed that high expression of Ki-67 and cyclin A is associated with more adverse tumor stage. The cutoff value for Ki-67 for distant metastases was set to 22% and to 15%, using hot-spot and average counting, respectively. For cyclin A, the values were set to 14% and 8% using the respective methods. Survival curves revealed that patients with a high hot-spot proliferation index had a significantly greater risk of shorter tumor-free survival. Our findings suggest that the determination of proliferation markers in breast cancer should be standardized to hot-spot counting and that specific cutoff values for proliferation could be useful as prognostic markers in clinical practice. Moreover, we suggest that expression levels of cyclin A could be used as a complementary marker to estimate the proliferation status in tumors, especially those with "borderline" expression levels of Ki-67, in order to more accurately estimate the proliferations status of the tumors.