Integrated proteomics identifies PARP inhibitor-induced prosurvival signaling changes as potential vulnerabilities in ovarian cancer.

BRCA1/2-deficient ovarian carcinoma (OC) has been shown to be particularly sensitive to poly (ADP-ribose) polymerase inhibitors (PARPis). Furthermore, BRCA1/2 mutation status is currently used as a predictive biomarker for PARPi therapy. Despite providing a major clinical benefit to the majority of patients, a significant proportion of BRCA1/2-deficient OC tumors do not respond to PARPis for reasons that are incompletely understood. Using an integrated chemical, phospho- and ADP-ribosylation proteomics approach, we sought here to develop additional mechanism-based biomarker candidates for PARPi therapy in OC and identify new targets for combination therapy to overcome primary resistance. Using chemical proteomics with PARPi baits in a BRCA1-isogenic OC cell line pair, as well as patient-derived BRCA1-proficient and BRCA1-deficient tumor samples, and subsequent validation by coimmunoprecipitation, we showed differential PARP1 and PARP2 protein complex composition in PARPi-sensitive, BRCA1-deficient UWB1.289 (UWB) cells compared to PARPi-insensitive, BRCA1-reconstituted UWB1.289+BRCA1 (UWB+B) cells. In addition, global phosphoproteomics and ADP-ribosylation proteomics furthermore revealed that the PARPi rucaparib induced the cell cycle pathway and nonhomologous end joining (NHEJ) pathway in UWB cells but downregulated ErbB signaling in UWB+B cells. In addition, we observed AKT PARylation and prosurvival AKT-mTOR signaling in UWB+B cells after PARPi treatment. Consistently, we found the synergy of PARPis with DNAPK or AKT inhibitors was more pronounced in UWB+B cells, highlighting these pathways as actionable vulnerabilities. In conclusion, we demonstrate the combination of chemical proteomics, phosphoproteomics, and ADP-ribosylation proteomics can identify differential PARP1/2 complexes and diverse, but actionable, drug compensatory signaling in OC.

Differential Chemoproteomics Reveals MARK2/3 as Cell Migration-Relevant Targets of the ALK Inhibitor Brigatinib.

Metastasis poses a major challenge in cancer management, including EML4-ALK-rearranged non-small cell lung cancer (NSCLC). As cell migration is a critical step during metastasis, we assessed the anti-migratory activities of several clinical ALK inhibitors in NSCLC cells and observed differential anti-migratory capabilities despite similar ALK inhibition, with brigatinib displaying superior anti-migratory effects over other ALK inhibitors. Applying an unbiased in situ mass spectrometry-based chemoproteomics approach, we determined the proteome-wide target profile of brigatinib in EML4-ALK+ NSCLC cells. Dose-dependent and cross-competitive chemoproteomics suggested MARK2 and MARK3 as relevant brigatinib kinase targets. Functional validation showed that combined pharmacological inhibition or genetic modulation of MARK2/3 inhibited cell migration. Consistently, brigatinib treatment induced inhibitory YAP1 phosphorylation downstream of MARK2/3. Collectively, our data suggest that brigatinib exhibits unusual cross-phenotype polypharmacology as, despite similar efficacy for inhibiting EML4-ALK-dependent cell proliferation as other ALK inhibitors, it more effectively prevented migration of NSCLC cells due to co-targeting of MARK2/3.

Turning liabilities into opportunities: Off-target based drug repurposing in cancer.

Targeted drugs and precision medicine have transformed the landscape of cancer therapy and significantly improved patient outcomes in many cases. However, as therapies are becoming more and more tailored to smaller patient populations and acquired resistance is limiting the duration of clinical responses, there is an ever increasing demand for new drugs, which is not easily met considering steadily rising drug attrition rates and development costs. Considering these challenges drug repurposing is an attractive complementary approach to traditional drug discovery that can satisfy some of these needs. This is facilitated by the fact that most targeted drugs, despite their implicit connotation, are not singularly specific, but rather display a wide spectrum of target selectivity. Importantly, some of the unintended drug "off-targets" are known anticancer targets in their own right. Others are becoming recognized as such in the process of elucidating off-target mechanisms that in fact are responsible for a drug's anticancer activity, thereby revealing potentially new cancer vulnerabilities. Harnessing such beneficial off-target effects can therefore lead to novel and promising precision medicine approaches. Here, we will discuss experimental and computational methods that are employed to specifically develop single target and network-based off-target repurposing strategies, for instance with drug combinations or polypharmacology drugs. By illustrating concrete examples that have led to clinical translation we will furthermore examine the various scientific and non-scientific factors that cumulatively determine the success of these efforts and thus can inform the future development of new and potentially lifesaving off-target based drug repurposing strategies for cancers that constitute important unmet medical needs.

Novel Human-Derived RET Fusion NSCLC Cell Lines Have Heterogeneous Responses to RET Inhibitors and Differential Regulation of Downstream Signaling.

Rearranged during transfection (RET) rearrangements occur in 1% to 2% of lung adenocarcinomas as well as other malignancies and are now established targets for tyrosine kinase inhibitors. We developed three novel RET fusion-positive (RET+) patient-derived cancer cell lines, CUTO22 [kinesin 5B (KIF5B)-RET fusion], CUTO32 (KIF5B-RET fusion), and CUTO42 (echinoderm microtubule-associated protein-like 4-RET fusion), to study RET signaling and response to therapy. We confirmed each of our cell lines expresses the RET fusion protein and assessed their sensitivity to RET inhibitors. We found that the CUTO22 and CUTO42 cell lines were sensitive to multiple RET inhibitors, whereas the CUTO32 cell line was >10-fold more resistant to three RET inhibitors. We discovered that our RET+ cell lines had differential regulation of the mitogen-activated protein kinase and phosphoinositide 3-kinase/protein kinase B (AKT) pathways. After inhibition of RET, the CUTO42 cells had robust inhibition of phosphorylated AKT (pAKT), whereas CUTO22 and CUTO32 cells had sustained AKT activation. Next, we performed a drug screen, which revealed that the CUTO32 cells were sensitive (<1 nM IC50) to inhibition of two cell cycle-regulating proteins, polo-like kinase 1 and Aurora kinase A. Finally, we show that two of these cell lines, CUTO32 and CUTO42, successfully establish xenografted tumors in nude mice. We demonstrated that the RET inhibitor BLU-667 was effective at inhibiting tumor growth in CUTO42 tumors but had a much less profound effect in CUTO32 tumors, consistent with our in vitro experiments. These data highlight the utility of new RET+ models to elucidate differences in response to tyrosine kinase inhibitors and downstream signaling regulation. Our RET+ cell lines effectively recapitulate the interpatient heterogeneity observed in response to RET inhibitors and reveal opportunities for alternative or combination therapies. SIGNIFICANCE STATEMENT: We have derived and characterized three novel rearranged during transfection (RET) fusion non-small cell lung cancer cell lines and demonstrated that they have differential responses to RET inhibition as well as regulation of downstream signaling, an area that has previously been limited by a lack of diverse cell line modes with endogenous RET fusions. These data offer important insight into regulation of response to RET tyrosine kinase inhibitors and other potential therapeutic targets.

Lowering Sample Requirements to Study Tyrosine Kinase Signaling Using Phosphoproteomics with the TMT Calibrator Approach.

Analysis of tyrosine kinase signaling is critical for the development of targeted cancer therapy. Currently, immunoprecipitation of phosphotyrosine (pY) peptides prior to liquid chromatography-tandem mass spectrometry (LC-MS/MS) is used to profile tyrosine kinase substrates. A typical protocol requests 10 mg of total protein from ≈108 cells or 50-100 mg of tissue. Large sample requirements can be cost prohibitive or not feasible for certain experiments. Sample multiplexing using chemical labeling reduces the protein amount required for each sample, and newer approaches use a material-rich reference channel as a calibrator to trigger detection and quantification for smaller samples. Here, it is demonstrated that the tandem mass tag (TMT) calibrator approach reduces the sample input for pY profiling tenfold (to ≈1 mg total protein per sample from 107 cells grown in one plate), while maintaining the depth of pY proteome sampling and the biological content of the experiment. Data are available through PRIDE (PXD019764 for label-free and PXD018952 for TMT). This strategy opens more opportunities for pY profiling of large sample cohorts and samples with limited protein quantity such as immune cells, xenograft models, and human tumors.

Functional Proteomics and Deep Network Interrogation Reveal a Complex Mechanism of Action of Midostaurin in Lung Cancer Cells.

Lung cancer is associated with high prevalence and mortality, and despite significant successes with targeted drugs in genomically defined subsets of lung cancer and immunotherapy, the majority of patients currently does not benefit from these therapies. Through a targeted drug screen, we found the recently approved multi-kinase inhibitor midostaurin to have potent activity in several lung cancer cells independent of its intended target, PKC, or a specific genomic marker. To determine the underlying mechanism of action we applied a layered functional proteomics approach and a new data integration method. Using chemical proteomics, we identified multiple midostaurin kinase targets in these cells. Network-based integration of these targets with quantitative tyrosine and global phosphoproteomics data using protein-protein interactions from the STRING database suggested multiple targets are relevant for the mode of action of midostaurin. Subsequent functional validation using RNA interference and selective small molecule probes showed that simultaneous inhibition of TBK1, PDPK1 and AURKA was required to elicit midostaurin's cellular effects. Immunoblot analysis of downstream signaling nodes showed that combined inhibition of these targets altered PI3K/AKT and cell cycle signaling pathways that in part converged on PLK1. Furthermore, rational combination of midostaurin with the potent PLK1 inhibitor BI2536 elicited strong synergy. Our results demonstrate that combination of complementary functional proteomics approaches and subsequent network-based data integration can reveal novel insight into the complex mode of action of multi-kinase inhibitors, actionable targets for drug discovery and cancer vulnerabilities. Finally, we illustrate how this knowledge can be used for the rational design of synergistic drug combinations with high potential for clinical translation.

Polypharmacology-based ceritinib repurposing using integrated functional proteomics.

Targeted drugs are effective when they directly inhibit strong disease drivers, but only a small fraction of diseases feature defined actionable drivers. Alternatively, network-based approaches can uncover new therapeutic opportunities. Applying an integrated phenotypic screening, chemical and phosphoproteomics strategy, here we describe the anaplastic lymphoma kinase (ALK) inhibitor ceritinib as having activity across several ALK-negative lung cancer cell lines and identify new targets and network-wide signaling effects. Combining pharmacological inhibitors and RNA interference revealed a polypharmacology mechanism involving the noncanonical targets IGF1R, FAK1, RSK1 and RSK2. Mutating the downstream signaling hub YB1 protected cells from ceritinib. Consistent with YB1 signaling being known to cause taxol resistance, combination of ceritinib with paclitaxel displayed strong synergy, particularly in cells expressing high FAK autophosphorylation, which we show to be prevalent in lung cancer. Together, we present a systems chemical biology platform for elucidating multikinase inhibitor polypharmacology mechanisms, subsequent design of synergistic drug combinations, and identification of mechanistic biomarker candidates.

Comparison of Quantitative Mass Spectrometry Platforms for Monitoring Kinase ATP Probe Uptake in Lung Cancer.

Recent developments in instrumentation and bioinformatics have led to new quantitative mass spectrometry platforms including LC-MS/MS with data-independent acquisition (DIA) and targeted analysis using parallel reaction monitoring mass spectrometry (LC-PRM), which provide alternatives to well-established methods, such as LC-MS/MS with data-dependent acquisition (DDA) and targeted analysis using multiple reaction monitoring mass spectrometry (LC-MRM). These tools have been used to identify signaling perturbations in lung cancers and other malignancies, supporting the development of effective kinase inhibitors and, more recently, providing insights into therapeutic resistance mechanisms and drug repurposing opportunities. However, detection of kinases in biological matrices can be challenging; therefore, activity-based protein profiling enrichment of ATP-utilizing proteins was selected as a test case for exploring the limits of detection of low-abundance analytes in complex biological samples. To examine the impact of different MS acquisition platforms, quantification of kinase ATP uptake following kinase inhibitor treatment was analyzed by four different methods: LC-MS/MS with DDA and DIA, LC-MRM, and LC-PRM. For discovery data sets, DIA increased the number of identified kinases by 21% and reduced missingness when compared with DDA. In this context, MRM and PRM were most effective at identifying global kinome responses to inhibitor treatment, highlighting the value of a priori target identification and manual evaluation of quantitative proteomics data sets. We compare results for a selected set of desthiobiotinylated peptides from PRM, MRM, and DIA and identify considerations for selecting a quantification method and postprocessing steps that should be used for each data acquisition strategy.

APOSTL: An Interactive Galaxy Pipeline for Reproducible Analysis of Affinity Proteomics Data.

With continuously increasing scale and depth of coverage in affinity proteomics (AP-MS) data, the analysis and visualization is becoming more challenging. A number of tools have been developed to identify high-confidence interactions; however, a cohesive and intuitive pipeline for analysis and visualization is still needed. Here we present Automated Processing of SAINT Templated Layouts (APOSTL), a freely available Galaxy-integrated software suite and analysis pipeline for reproducible, interactive analysis of AP-MS data. APOSTL contains a number of tools woven together using Galaxy workflows, which are intuitive for the user to move from raw data to publication-quality figures within a single interface. APOSTL is an evolving software project with the potential to customize individual analyses with additional Galaxy tools and widgets using the R web application framework, Shiny. The source code, data, and documentation are freely available from GitHub ( https://github.com/bornea/APOSTL ) and other sources.

Targeting a cell state common to triple-negative breast cancers.

Some mutations in cancer cells can be exploited for therapeutic intervention. However, for many cancer subtypes, including triple-negative breast cancer (TNBC), no frequently recurring aberrations could be identified to make such an approach clinically feasible. Characterized by a highly heterogeneous mutational landscape with few common features, many TNBCs cluster together based on their 'basal-like' transcriptional profiles. We therefore hypothesized that targeting TNBC cells on a systems level by exploiting the transcriptional cell state might be a viable strategy to find novel therapies for this highly aggressive disease. We performed a large-scale chemical genetic screen and identified a group of compounds related to the drug PKC412 (midostaurin). PKC412 induced apoptosis in a subset of TNBC cells enriched for the basal-like subtype and inhibited tumor growth in vivo. We employed a multi-omics approach and computational modeling to address the mechanism of action and identified spleen tyrosine kinase (SYK) as a novel and unexpected target in TNBC. Quantitative phosphoproteomics revealed that SYK inhibition abrogates signaling to STAT3, explaining the selectivity for basal-like breast cancer cells. This non-oncogene addiction suggests that chemical SYK inhibition may be beneficial for a specific subset of TNBC patients and demonstrates that targeting cell states could be a viable strategy to discover novel treatment strategies.

Evaluating kinase ATP uptake and tyrosine phosphorylation using multiplexed quantification of chemically labeled and post-translationally modified peptides.

Cancer biologists and other healthcare researchers face an increasing challenge in addressing the molecular complexity of disease. Biomarker measurement tools and techniques now contribute to both basic science and translational research. In particular, liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) for multiplexed measurements of protein biomarkers has emerged as a versatile tool for systems biology. Assays can be developed for specific peptides that report on protein expression, mutation, or post-translational modification; discovery proteomics data rapidly translated into multiplexed quantitative approaches. Complementary advances in affinity purification enrich classes of enzymes or peptides representing post-translationally modified or chemically labeled substrates. Here, we illustrate the process for the relative quantification of hundreds of peptides in a single LC-MRM experiment. Desthiobiotinylated peptides produced by activity-based protein profiling (ABPP) using ATP probes and tyrosine-phosphorylated peptides are used as examples. These targeted quantification panels can be applied to further understand the biology of human disease.

Dissection of TBK1 signaling via phosphoproteomics in lung cancer cells.

TANK-binding kinase 1 (TBK1) has emerged as a novel therapeutic target for unspecified subset of lung cancers. TBK1 reportedly mediates prosurvival signaling by activating NF-κB and AKT. However, we observed that TBK1 knockdown also decreased viability of cells expressing constitutively active NF-κB and interferon regulatory factor 3. Basal phospho-AKT level was not reduced after TBK1 knockdown in TBK1-sensitive lung cancer cells, implicating that TBK1 mediates unknown survival mechanisms. To gain better insight into TBK1 survival signaling, we searched for altered phosphoproteins using mass spectrometry following RNAi-mediated TBK1 knockdown. In total, we identified 2,080 phosphoproteins (4,621 peptides), of which 385 proteins (477 peptides) were affected after TBK1 knockdown. A view of the altered network identified a central role of Polo-like kinase 1 (PLK1) and known PLK1 targets. We found that TBK1 directly phosphorylated PLK1 in vitro. TBK1 phosphorylation was induced at mitosis, and loss of TBK1 impaired mitotic phosphorylation of PLK1 in TBK1-sensitive lung cancer cells. Furthermore, lung cancer cell sensitivity to TBK1 was highly correlated with sensitivity to pharmacological PLK inhibition. We additionally found that TBK1 knockdown decreased metadherin phosphorylation at Ser-568. Metadherin was associated with poor outcome in lung cancer, and loss of metadherin caused growth inhibition and apoptosis in TBK1-sensitive lung cancer cells. These results collectively revealed TBK1 as a mitosis regulator through activation of PLK1 and also suggested metadherin as a putative TBK1 downstream effector involved in lung cancer cell survival.

Perturbation of the mutated EGFR interactome identifies vulnerabilities and resistance mechanisms.

We hypothesized that elucidating the interactome of epidermal growth factor receptor (EGFR) forms that are mutated in lung cancer, via global analysis of protein-protein interactions, phosphorylation, and systematically perturbing the ensuing network nodes, should offer a new, more systems-level perspective of the molecular etiology. Here, we describe an EGFR interactome of 263 proteins and offer a 14-protein core network critical to the viability of multiple EGFR-mutated lung cancer cells. Cells with acquired resistance to EGFR tyrosine kinase inhibitors (TKIs) had differential dependence of the core network proteins based on the underlying molecular mechanisms of resistance. Of the 14 proteins, 9 are shown to be specifically associated with survival of EGFR-mutated lung cancer cell lines. This included EGFR, GRB2, MK12, SHC1, ARAF, CD11B, ARHG5, GLU2B, and CD11A. With the use of a drug network associated with the core network proteins, we identified two compounds, midostaurin and lestaurtinib, that could overcome drug resistance through direct EGFR inhibition when combined with erlotinib. Our results, enabled by interactome mapping, suggest new targets and combination therapies that could circumvent EGFR TKI resistance.

Systems-pharmacology dissection of a drug synergy in imatinib-resistant CML.

Occurrence of the BCR-ABL(T315I) gatekeeper mutation is among the most pressing challenges in the therapy of chronic myeloid leukemia (CML). Several BCR-ABL inhibitors have multiple targets and pleiotropic effects that could be exploited for their synergistic potential. Testing combinations of such kinase inhibitors identified a strong synergy between danusertib and bosutinib that exclusively affected CML cells harboring BCR-ABL(T315I). To elucidate the underlying mechanisms, we applied a systems-level approach comprising phosphoproteomics, transcriptomics and chemical proteomics. Data integration revealed that both compounds targeted Mapk pathways downstream of BCR-ABL, resulting in impaired activity of c-Myc. Using pharmacological validation, we assessed that the relative contributions of danusertib and bosutinib could be mimicked individually by Mapk inhibitors and collectively by downregulation of c-Myc through Brd4 inhibition. Thus, integration of genome- and proteome-wide technologies enabled the elucidation of the mechanism by which a new drug synergy targets the dependency of BCR-ABL(T315I) CML cells on c-Myc through nonobvious off targets.

PTEN Lipid Phosphatase Activity Suppresses Melanoma Formation by Opposing an AKT/mTOR/FRA1 Signaling Axis.

Inactivating mutations in PTEN are prevalent in melanoma and are thought to support tumor development by hyperactivating the AKT/mTOR pathway. Conversely, activating mutations in AKT are relatively rare in melanoma, and therapies targeting AKT or mTOR have shown disappointing outcomes in preclinical models and clinical trials of melanoma. This has led to the speculation that PTEN suppresses melanoma by opposing AKT-independent pathways, potentially through noncanonical functions beyond its lipid phosphatase activity. In this study, we examined the mechanisms of PTEN-mediated suppression of melanoma formation through the restoration of various PTEN functions in PTEN-deficient cells or mouse models. PTEN lipid phosphatase activity predominantly inhibited melanoma cell proliferation, invasion, and tumor growth, with minimal contribution from its protein phosphatase and scaffold functions. A drug screen underscored the exquisite dependence of PTEN-deficient melanoma cells on the AKT/mTOR pathway. Furthermore, activation of AKT alone was sufficient to counteract several aspects of PTEN-mediated melanoma suppression, particularly invasion and the growth of allograft tumors. Phosphoproteomics analysis of the lipid phosphatase activity of PTEN validated its potent inhibition of AKT and many of its known targets, while also identifying the AP-1 transcription factor FRA1 as a downstream effector. The restoration of PTEN dampened FRA1 translation by inhibiting AKT/mTOR signaling, and FRA1 overexpression negated aspects of PTEN-mediated melanoma suppression akin to AKT. This study supports AKT as the key mediator of PTEN inactivation in melanoma and identifies an AKT/mTOR/FRA1 axis as a driver of melanomagenesis. SIGNIFICANCE: PTEN suppresses melanoma predominantly through its lipid phosphatase function, which when lost, elevates FRA1 levels through AKT/mTOR signaling to promote several aspects of melanomagenesis.

Differential network analysis of ROS1 inhibitors reveals lorlatinib polypharmacology through co-targeting PYK2.

Multiple tyrosine kinase inhibitors (TKIs) are often developed for the same indication. However, their relative overall efficacy is frequently incompletely understood and they may harbor unrecognized targets that cooperate with the intended target. We compared several ROS1 TKIs for inhibition of ROS1-fusion-positive lung cancer cell viability, ROS1 autophosphorylation and kinase activity, which indicated disproportionately higher cellular potency of one TKI, lorlatinib. Quantitative chemical and phosphoproteomics across four ROS1 TKIs and differential network analysis revealed that lorlatinib uniquely impacted focal adhesion signaling. Functional validation using pharmacological probes, RNA interference, and CRISPR-Cas9 knockout uncovered a polypharmacology mechanism of lorlatinib by dual targeting ROS1 and PYK2, which form a multiprotein complex with SRC. Rational multi-targeting of this complex by combining lorlatinib with SRC inhibitors exhibited pronounced synergy. Taken together, we show that systems pharmacology-based differential network analysis can dissect mixed canonical/non-canonical polypharmacology mechanisms across multiple TKIs enabling the design of rational drug combinations.

Cancer-associated fibroblasts confer ALK inhibitor resistance in EML4-ALK -driven lung cancer via concurrent integrin and MET signaling.

Cancer-associated fibroblasts (CAFs) are associated with tumor progression and modulate drug sensitivity of cancer cells. However, the underlying mechanisms are often incompletely understood and crosstalk between tumor cells and CAFs involves soluble secreted as well as adhesion proteins. Interrogating a panel of non-small cell lung cancer (NSCLC) cell lines driven by EML4-ALK fusions, we observed substantial CAF-mediated drug resistance to clinical ALK tyrosine kinase inhibitors (TKIs). Array-based cytokine profiling of fibroblast-derived conditioned- media identified HGF-MET signaling as a major contributor to CAF-mediated paracrine resistance that can be overcome by MET TKIs. However, 'Cell Type specific labeling using Amino acid Precursors' (CTAP)-based expression and phosphoproteomics in direct coculture also highlighted a critical role for the fibronectin-integrin pathway. Flow cytometry analysis confirmed activation of integrin ß1 (ITGB1) in lung cancer cells by CAF coculture. Treatment with pharmacological inhibitors, cancer cell-specific silencing or CRISPR-Cas9-mediated knockout of ITGB1 overcame adhesion protein-mediated resistance. Concurrent targeting of MET and integrin signaling effectively abrogated CAF-mediated resistance of EML4-ALK -driven NSCLC cells to ALK TKIs in vitro . Consistently, combination of the ALK TKI alectinib with the MET TKI capmatinib and/or the integrin inhibitor cilengitide was significantly more efficacious than single agent treatment in suppressing tumor growth using an in vivo EML4-ALK -dependent allograft mouse model of NSCLC. In summary, these findings emphasize the complexity of resistance-associated crosstalk between CAFs and cancer cells, which can involve multiple concurrent signaling pathways, and illustrate how comprehensive elucidation of paracrine and juxtacrine resistance mechanisms can inform on more effective therapeutic approaches.

A miniaturized chemical proteomic approach for target profiling of clinical kinase inhibitors in tumor biopsies.

While targeted therapy based on the idea of attenuating the activity of a preselected, therapeutically relevant protein has become one of the major trends in modern cancer therapy, no truly specific targeted drug has been developed and most clinical agents have displayed a degree of polypharmacology. Therefore, the specificity of anticancer therapeutics has emerged as a highly important but severely underestimated issue. Chemical proteomics is a powerful technique combining postgenomic drug-affinity chromatography with high-end mass spectrometry analysis and bioinformatic data processing to assemble a target profile of a desired therapeutic molecule. Due to high demands on the starting material, however, chemical proteomic studies have been mostly limited to cancer cell lines. Herein, we report a down-scaling of the technique to enable the analysis of very low abundance samples, as those obtained from needle biopsies. By a systematic investigation of several important parameters in pull-downs with the multikinase inhibitor bosutinib, the standard experimental protocol was optimized to 100 µg protein input. At this level, more than 30 well-known targets were detected per single pull-down replicate with high reproducibility. Moreover, as presented by the comprehensive target profile obtained from miniaturized pull-downs with another clinical drug, dasatinib, the optimized protocol seems to be extendable to other drugs of interest. Sixty distinct human and murine targets were finally identified for bosutinib and dasatinib in chemical proteomic experiments utilizing core needle biopsy samples from xenotransplants derived from patient tumor tissue. Altogether, the developed methodology proves robust and generic and holds many promises for the field of personalized health care.